Dr. Thia Kirubarajan Profile

Dr. Thia Kirubarajan

President at TrackGen Solutions Inc.

SPIE Involvement:

Conference Co-Chair | Author

Publications (123)

Proceedings Article | 2 May 2017 Paper

Development of a variable structure-based fault detection and diagnosis strategy applied to an electromechanical system

S. Andrew Gadsden, T. Kirubarajan

Proceedings Volume 10200, 102001E (2017) https://doi.org/10.1117/12.2262570

KEYWORDS: Error analysis, Systems modeling, Switching, Matrices, Control systems, Filtering (signal processing), Signal processing, Actuators

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Proceedings Article | 17 May 2016 Paper

B-spline based image tracking by detection

Bhashyam Balaji, Rajiv Sithiravel, Anthony Damini, Thiagalingam Kirubarajan, Sreeraman Rajan

Proceedings Volume 9842, 984202 (2016) https://doi.org/10.1117/12.2228248

KEYWORDS: Optical tracking, Motion models, Detection and tracking algorithms, Visualization, Image visualization, Roads, Optical tracking, Target detection, Cameras, Motion estimation, Surveillance

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Proceedings Article | 22 May 2015 Paper

Radar resource management for a ground moving target indication radar

Bhashyam Balaji, Rajiv Sithiravel, Anthony Damini, Kai Wang, Thiagalingam Kirubarajan

Proceedings Volume 9474, 947402 (2015) https://doi.org/10.1117/12.2179287

KEYWORDS: Radar, Synthetic aperture radar, Sensors, Error analysis, Target detection, Antennas, Automatic tracking, Doppler effect, Performance modeling, Personal digital assistants

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Proceedings Article | 21 May 2015 Paper

Two-pass smoother based on the SVSF estimation strategy

S. Gadsden, Mohammad AlShabi, T. Kirubarajan

Proceedings Volume 9474, 947409 (2015) https://doi.org/10.1117/12.2177256

KEYWORDS: Filtering (signal processing), Actuators, Error analysis, Aerospace engineering, Systems modeling, Complex systems, Matrices, Switching, Electronic filtering, Monte Carlo methods

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Proceedings Article | 21 May 2015 Paper

Aspects of detection and tracking of ground targets from an airborne EO/IR sensor

Bhashyam Balaji, Rajiv Sithiravel, Zahir Daya, Thiagalingam Kirubarajan

Proceedings Volume 9474, 947403 (2015) https://doi.org/10.1117/12.2179283

KEYWORDS: Sensors, Target detection, Infrared sensors, Motion models, Cameras, Imaging systems, Image sensors, Detection and tracking algorithms, Optical tracking, Image fusion

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Proceedings Article | 21 May 2015 Paper

Square-root formulation of the SVSF with applications to nonlinear target tracking problems

S. Gadsden, Mohammad AlShabi, T. Kirubarajan

Proceedings Volume 9474, 947408 (2015) https://doi.org/10.1117/12.2177226

KEYWORDS: Filtering (signal processing), Error analysis, Complex systems, Detection and tracking algorithms, Electronic filtering, Nonlinear filtering, Numerical stability, Matrices, Sensors, Switching

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SPIE Journal Paper | 13 May 2015 Open Access

Active vehicle protection using angle and time-to-go information from high-resolution infrared sensors

Ihsan Ullah, Taek Lyul Song, Thia Kirubarajan

OE, Vol. 54, Issue 05, 053110, (May 2015) https://doi.org/10.1117/12.10.1117/1.OE.54.5.053110

KEYWORDS: Sensors, Infrared sensors, Radar, Signal to noise ratio, Detection and tracking algorithms, Passive sensors, Filtering (signal processing), Optical engineering, Ranging, Computer simulations

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Proceedings Article | 18 May 2012 Paper

MeMBer filter for manoeuvring targets

Darcy Dunne, T. Kirubarajan

Proceedings Volume 8392, 839205 (2012) https://doi.org/10.1117/12.921069

KEYWORDS: Motion models, Berkelium, Digital filtering, Target detection, Nonlinear filtering, Electronic filtering, Mathematical modeling, Filtering (signal processing), Gaussian filters, Motion measurement

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Proceedings Article | 18 May 2012 Paper

A Gaussian mixture filter for target tracking with Doppler ambiguity

Gongjian Zhou, Michel Pelletier, Thiagalingam Kirubarajan, Taifan Quan

Proceedings Volume 8392, 839206 (2012) https://doi.org/10.1117/12.921298

KEYWORDS: Doppler effect, Gaussian filters, Filtering (signal processing), Electronic filtering, Radar, Monte Carlo methods, Signal processing, Digital filtering, Time metrology, Nonlinear filtering

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Proceedings Article | 18 May 2012 Paper

Simulation of large-scale multitarget tracking scenarios using GPUs

Yusuf Dinath, R. Tharmarasa, Eric Meger, Pierre Valin, T. Kirubarajan

Proceedings Volume 8392, 839209 (2012) https://doi.org/10.1117/12.921043

KEYWORDS: Detection and tracking algorithms, Motion models, Computer simulations, Monte Carlo methods, Computer programming, Roads, Surveillance, Mathematics, Target recognition, Statistical modeling

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Proceedings Article | 18 May 2012 Paper

The spline probability hypothesis density filter

Rajiv Sithiravel, Ratnasingham Tharmarasa, Mike McDonald, Michel Pelletier, Thiagalingam Kirubarajan

Proceedings Volume 8392, 83920E (2012) https://doi.org/10.1117/12.921022

KEYWORDS: Digital filtering, Nonlinear filtering, Electronic filtering, Particles, Gaussian filters, Filtering (signal processing), Monte Carlo methods, Systems modeling, Linear filtering, Particle filters

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Proceedings Article | 15 May 2012 Paper

Prediction, tracking, and retrodiction for path-constrained targets

K. Krishanth, R. Tharmarasa, T. Kirubarajan, P. Valin, E. Meger

Proceedings Volume 8393, 83930O (2012) https://doi.org/10.1117/12.921035

KEYWORDS: Detection and tracking algorithms, Motion models, Algorithm development, Image segmentation, Sensors, Electronic filtering, Monte Carlo methods, Process modeling, Forensic science, Motion analysis

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Proceedings Article | 15 May 2012 Paper

Measurement level AIS/radar fusion for maritime surveillance

Biruk Habtemariam, R. Tharmarasa, Eric Meger, T. Kirubarajan

Proceedings Volume 8393, 83930I (2012) https://doi.org/10.1117/12.920156

KEYWORDS: Artificial intelligence, Radar, Maritime surveillance, Data fusion, Surveillance, Detection and tracking algorithms, Motion models, Time metrology, Head, System identification

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Proceedings Article | 17 September 2011 Paper

Performance evaluations of multipath multitarget tracking using PCRLB

M. Subramaniam, K. Punithakumar, R. Tharmarasa, M. McDonald, T. Kirubarajan

Proceedings Volume 8137, 813714 (2011) https://doi.org/10.1117/12.894926

KEYWORDS: Reflection, Sensors, Transmitters, Receivers, Detection and tracking algorithms, Radar, Environmental sensing, Target detection, Picosecond phenomena, Remote sensing

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Proceedings Article | 17 September 2011 Paper

Improved multiframe association for tracking maneuvering targets

Biruk Habtemariam, R. Tharmarasa, N. Nandakumaran, M. McDonald, T. Kirubarajan

Proceedings Volume 8137, 81370O (2011) https://doi.org/10.1117/12.896465

KEYWORDS: Target detection, Data modeling, Detection and tracking algorithms, Motion models, Algorithm development, Motion estimation, Computer simulations, Motion measurement, Signal processing, Data processing

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Proceedings Article | 17 September 2011 Paper

Automatic track initialization and maintenance in heavy clutter using integrated JPDA and ML-PDA algorithms

K. Harishan, R. Tharmarasa, T. Kirubarajan, T. Thayaparan

Proceedings Volume 8137, 81370Q (2011) https://doi.org/10.1117/12.897438

KEYWORDS: Detection and tracking algorithms, Sensors, Target detection, Automatic tracking, Evolutionary algorithms, Distance measurement, Signal to noise ratio, Motion models, Error analysis, Monte Carlo methods

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Proceedings Article | 17 September 2011 Paper

Dynamic sector processing using 2D assignment for rotating radars

Biruk Habtemariam, R. Tharmarasa, M. Pelletier, T. Kirubarajan

Proceedings Volume 8137, 81370U (2011) https://doi.org/10.1117/12.896492

KEYWORDS: Radar, Detection and tracking algorithms, Tin, Data processing, Sensors, Antennas, Target detection, Systems modeling, Phased arrays, Time metrology

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Proceedings Article | 5 May 2011 Paper

Application of the smooth variable structure filter to a multi-target tracking problem

S. Gadsden, D. Dunne, R. Tharmarasa, S. R. Habibi, T. Kirubarajan

Proceedings Volume 8050, 805009 (2011) https://doi.org/10.1117/12.884063

KEYWORDS: Filtering (signal processing), Electronic filtering, Complex systems, Error analysis, Signal processing, Ions, Statistical analysis, Nonlinear filtering, Sensors, Neodymium

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Proceedings Article | 28 April 2010 Paper

Integrated clutter estimation and target tracking using JIPDA/MHT tracker

Xin Chen, R. Tharmarasa, T. Kirubarajan, Michel Pelletier

Proceedings Volume 7697, 769703 (2010) https://doi.org/10.1117/12.851048

KEYWORDS: Detection and tracking algorithms, Surveillance, Filtering (signal processing), Data integration, Electronic filtering, Computer simulations, Target detection, Superposition, Picosecond phenomena, Process modeling

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Proceedings Article | 28 April 2010 Paper

A generalized evidence conflict measure

Yaowen Fu, Wei Yang, Yuping Jia, T. Kirubarajan

Proceedings Volume 7697, 76971L (2010) https://doi.org/10.1117/12.851516

KEYWORDS: Distance measurement, Numerical simulations, Artificial intelligence, Electronics engineering, Defense technologies, Computer engineering, Computer simulations, Signal processing, Sensor fusion, Target recognition

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Proceedings Article | 28 April 2010 Paper

An assignment based algorithm for multiple target localization problems using widely-separated MIMO radars

A. A. Gorji, R. Tharmarasa, T. Kirubarajan

Proceedings Volume 7697, 769702 (2010) https://doi.org/10.1117/12.851051

KEYWORDS: Radar, Signal to noise ratio, Detection and tracking algorithms, Antennas, Receivers, Transmitters, Target detection, Electronic filtering, Surveillance, Signal generators

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Proceedings Article | 16 April 2010 Paper

Two-level automatic multiple target joint tracking and classification

Xiaofan He, Ratnasingham Tharmarasa, Michael Pelletier, Thia Kirubarajan

Proceedings Volume 7698, 76980O (2010) https://doi.org/10.1117/12.851068

KEYWORDS: Detection and tracking algorithms, Kinematics, Automatic tracking, Monte Carlo methods, Radar, Classification systems, Target recognition, Motion models, Surveillance, Particles

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Proceedings Article | 16 April 2010 Paper

Probabilistic data association in high clutter environments

R. Tharmarasa, T. Lang, Mike McDonald, T. Kirubarajan

Proceedings Volume 7698, 76980L (2010) https://doi.org/10.1117/12.851070

KEYWORDS: Personal digital assistants, Target detection, Filtering (signal processing), Surveillance, Time metrology, Electronic filtering, Sensors, Digital filtering, Algorithm development, Detection and tracking algorithms

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Proceedings Article | 16 April 2010 Paper

Multipath-assisted multitarget tracking with reflection point uncertainty

M. Subramaniam, R. Tharmarasa, M. McDonald, T. Kirubarajan

Proceedings Volume 7698, 76981A (2010) https://doi.org/10.1117/12.851118

KEYWORDS: Reflection, Sensors, Transmitters, Receivers, Detection and tracking algorithms, Picosecond phenomena, Remote sensing, Radar, Target detection, Defense and security

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Proceedings Article | 16 April 2010 Paper

Spline filter for target tracking

Donna Kocherry, R. Tharmarasa, Tom Lang, T. Kirubarajan

Proceedings Volume 7698, 76980H (2010) https://doi.org/10.1117/12.851075

KEYWORDS: Nonlinear filtering, Electronic filtering, Particles, Particle filters, Digital filtering, Detection and tracking algorithms, Filtering (signal processing), Time metrology, Motion measurement, Motion controllers

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Proceedings Article | 4 September 2009 Paper

EM-based Gaussian mixture model estimation for GMTI-based tracking using speedboat data

David Akselrod, Michael McDonald, T. Kirubarajan

Proceedings Volume 7445, 744511 (2009) https://doi.org/10.1117/12.827056

KEYWORDS: Data modeling, Radar, Data processing, Signal processing, Global Positioning System, Expectation maximization algorithms, Target detection, Data conversion, Binary data, Mathematical morphology

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Proceedings Article | 4 September 2009 Paper

Integrated clutter estimation and target tracking using Poisson point process

Xin Chen, R. Tharmarasa, T. Kirubarajan, Michel Pelletier

Proceedings Volume 7445, 74450X (2009) https://doi.org/10.1117/12.826140

KEYWORDS: Statistical analysis, Surveillance, Electronic filtering, Digital filtering, Computer simulations, Particles, Target detection, Detection and tracking algorithms, Infrared sensors, Sensors

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Proceedings Article | 4 September 2009 Paper

Feasibility of using transmitters of opportunity for precision multitarget tracking

N. Nandakumaran, R. Tharmarasa, Mike McDonald, T. Kirubarajan

Proceedings Volume 7445, 744512 (2009) https://doi.org/10.1117/12.827054

KEYWORDS: Receivers, Transmitters, 3D metrology, Detection and tracking algorithms, 3D acquisition, Target detection, Sensors, Signal to noise ratio, Radar, Fiber optic illuminators

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Proceedings Article | 4 September 2009 Paper

Multipath-assisted multitarget tracking using multiframe assignment

M. Subramaniam, R. Tharmarasa, M. Pelletier, T. Kirubarajan

Proceedings Volume 7445, 74450Z (2009) https://doi.org/10.1117/12.830470

KEYWORDS: Reflection, Sensors, Detection and tracking algorithms, Target detection, Receivers, Transmitters, Radar, Signal detection, Filtering (signal processing), Systems modeling

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Proceedings Article | 3 September 2009 Paper

Distributed tracking with probability hypothesis density filters using efficient measurement encoding

A. Aravinthan, R. Tharmarasa, Tom Lang, Mike McDonald, T. Kirubarajan

Proceedings Volume 7445, 74450H (2009) https://doi.org/10.1117/12.826552

KEYWORDS: Quantization, Computer programming, Sensor networks, Sensors, Detection and tracking algorithms, Monte Carlo methods, Particles, Electronic filtering, Computer simulations, Associative arrays

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Proceedings Article | 3 September 2009 Paper

Comparison of extended and unscented Kalman, particle, and smooth variable structure filters on a bearing-only target tracking problem

S. Gadsden, D. Dunne, S. Habibi, T. Kirubarajan

Proceedings Volume 7445, 74450B (2009) https://doi.org/10.1117/12.825424

KEYWORDS: Error analysis, Particles, Filtering (signal processing), Nonlinear filtering, Complex systems, Electronic filtering, Systems modeling, Sensors, Particle filters, Matrices

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Proceedings Article | 3 September 2009 Paper

Rao-Blackwellised approximate conditional mean probability hypothesis density filtering

N. Nandakumaran, S. Sutharsan, R. Tharmarasa, T. Lang, T. Kirubarajan

Proceedings Volume 7445, 74450J (2009) https://doi.org/10.1117/12.826423

KEYWORDS: Particles, Digital filtering, Neptunium, Gaussian filters, Detection and tracking algorithms, Nonlinear filtering, Sensors, Monte Carlo methods, Electronic filtering, Target detection

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Proceedings Article | 3 September 2009 Paper

Assignment-based particle labeling for PHD particle filter

Daniel Danu, Thomas Lang, Thia Kirubarajan

Proceedings Volume 7445, 74450D (2009) https://doi.org/10.1117/12.826203

KEYWORDS: Particles, Clouds, Particle filters, Filtering (signal processing), Electronic filtering, Detection and tracking algorithms, Target detection, Error analysis, Digital filtering, Data hiding

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Proceedings Article | 3 September 2009 Paper

SMC-PHD-based multi-target tracking with reduced peak extraction

Darcy Dunne, Ratnasingham Tharmarasa, Thomas Lang, T. Kirubarajan

Proceedings Volume 7445, 74450F (2009) https://doi.org/10.1117/12.826244

KEYWORDS: Particles, Electronic filtering, Digital filtering, Fuzzy logic, Detection and tracking algorithms, Target detection, Monte Carlo methods, Particle filters, Nonlinear filtering, Kinematics

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Proceedings Article | 1 September 2009 Paper

Interacting multiple model forward filtering and backward smoothing for maneuvering target tracking

N. Nandakumaran, S. Sutharsan, R. Tharmarasa, Tom Lang, Mike McDonald, T. Kirubarajan

Proceedings Volume 7445, 744503 (2009) https://doi.org/10.1117/12.826549

KEYWORDS: Smoothing, Detection and tracking algorithms, Electronic filtering, Motion models, Switching, Systems modeling, Performance modeling, Target detection, Time metrology, Computer simulations

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Proceedings Article | 1 September 2009 Paper

Event-based characterization and simulation of sea clutter

Michael McDonald, Darcy Dunne, Anthony Damini, Thiagalingam Kirubarajan

Proceedings Volume 7445, 744505 (2009) https://doi.org/10.1117/12.826128

KEYWORDS: Radar, Scattering, Antennas, Speckle, Target detection, Signal processing, Stochastic processes, Convolution, Image filtering, Data modeling

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Proceedings Article | 1 September 2009 Paper

Resolving transmitter-of-opportunity origin uncertainty in passive coherent location systems

R. Tharmarasa, N. Nandakumaran, Mike McDonald, T. Kirubarajan

Proceedings Volume 7445, 744506 (2009) https://doi.org/10.1117/12.826410

KEYWORDS: Transmitters, Receivers, Detection and tracking algorithms, Radar, Fermium, Frequency modulation, Logic, Surveillance, Fiber optic illuminators, Time metrology

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Proceedings Article | 24 August 2009 Paper

MIMO vs. multistatic radars for target localization

A. Gorji, R. Tharmarasa, T. Kirubarajan

Proceedings Volume 7445, 744502 (2009) https://doi.org/10.1117/12.826109

KEYWORDS: Radar, Signal to noise ratio, Transmitters, Target detection, Receivers, Detection and tracking algorithms, Signal processing, Antennas, Filtering (signal processing), Surveillance

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Proceedings Article | 11 May 2009 Paper

Maneuvering target tracking using probability hypothesis density smoothing

N. Nadarajah, T. Kirubarajan

Proceedings Volume 7336, 73360F (2009) https://doi.org/10.1117/12.817630

KEYWORDS: Digital filtering, Filtering (signal processing), Nonlinear filtering, Monte Carlo methods, Detection and tracking algorithms, Particles, Smoothing, Electronic filtering, Computer simulations, Target detection

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Proceedings Article | 11 May 2009 Paper

Improved target tracking using kinematic measurements and target orientation information

S. Sutharsan, R. Tharmarasa, T. Kirubarajan

Proceedings Volume 7336, 733604 (2009) https://doi.org/10.1117/12.819234

KEYWORDS: Sensors, Kinematics, Detection and tracking algorithms, Motion models, Monte Carlo methods, Algorithm development, Missiles, Motion estimation, Motion measurement, Radar

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Proceedings Article | 4 May 2009 Paper

A judicious multiple hypothesis tracker with interacting feature extraction

James McAnanama, T. Kirubarajan

Proceedings Volume 7338, 73380H (2009) https://doi.org/10.1117/12.818262

KEYWORDS: Feature extraction, Target detection, Principal component analysis, Surveillance, Kinematics, Electronic filtering, Signal processing, Image segmentation, Sensors, Filtering (signal processing)

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Proceedings Article | 17 April 2008 Paper

Gaussian mixture probability hypothesis density smoothing with multistatic sonar

N. Nandakumaran, R. Tharmarasa, T. Lang, T. Kirubarajan

Proceedings Volume 6968, 696807 (2008) https://doi.org/10.1117/12.779236

KEYWORDS: Detection and tracking algorithms, Filtering (signal processing), Gaussian filters, Algorithm development, Smoothing, Sensors, Active sonar, Electronic filtering, Monte Carlo methods, Doppler effect

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Proceedings Article | 17 April 2008 Paper

Tracking and classification using aspect-dependent RCS and kinematic data

S. Sutharsan, R. Tharmarasa, T. Lang, T. Kirubarajan

Proceedings Volume 6969, 696913 (2008) https://doi.org/10.1117/12.779218

KEYWORDS: Sensors, Kinematics, Radar, Detection and tracking algorithms, Motion models, Computer simulations, Data integration, Distance measurement, Data fusion, Scatter measurement

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Proceedings Article | 17 April 2008 Paper

Collaborative distributed sensor management and information exchange flow control for multitarget tracking using Markov decision processes

Dimitry Akselrod, T. Kirubarajan

Proceedings Volume 6968, 69680E (2008) https://doi.org/10.1117/12.779348

KEYWORDS: Unmanned aerial vehicles, Target detection, Sensors, Surveillance, Data fusion, Information fusion, Monte Carlo methods, Detection and tracking algorithms, Error analysis, Data processing

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Proceedings Article | 16 April 2008 Paper

Passive tracking with sensors of opportunity using passive coherent location

Mahes Subramaniam, R. Tharmarasa, Mike McDonald, T. Kirubarajan

Proceedings Volume 6969, 69691F (2008) https://doi.org/10.1117/12.779598

KEYWORDS: Filtering (signal processing), Particles, Radar, Transmitters, Receivers, Target detection, Doppler effect, Sensors, Particle filters, FM band

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Proceedings Article | 16 April 2008 Paper

Spline filter for multidimensional nonlinear/non-Gaussian Bayesian tracking

K. Punithakumar, Mike McDonald, T. Kirubarajan

Proceedings Volume 6969, 69690K (2008) https://doi.org/10.1117/12.779223

KEYWORDS: Nonlinear filtering, Electronic filtering, Digital filtering, Detection and tracking algorithms, Monte Carlo methods, Computer simulations, Filtering (signal processing), Defense and security, Numerical analysis, Process modeling

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Proceedings Article | 16 April 2008 Paper

Efficient data association for move-stop-move target tracking

T. Sathyan, Mike McDonald, T. Kirubarajan

Proceedings Volume 6969, 696917 (2008) https://doi.org/10.1117/12.779403

KEYWORDS: Detection and tracking algorithms, Target detection, Radar, Motion models, Algorithm development, Monte Carlo methods, Computer simulations, Motion measurement, Binary data, Environmental sensing

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Proceedings Article | 16 April 2008 Paper

Track fusion with feedback for local trackers using MHT

Daniel Danu, Tom Lang, T. Kirubarajan

Proceedings Volume 6969, 69690Y (2008) https://doi.org/10.1117/12.777851

KEYWORDS: Sensors, Error analysis, Statistical analysis, Time metrology, Target detection, Information fusion, Sensor fusion, Stars, Data fusion, Binary data

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Proceedings Article | 16 April 2008 Paper

Integrated bias removal in passive radar systems

M. Subramaniam, K. Punithakumar, M. McDonald, T. Kirubarajan

Proceedings Volume 6969, 69690Q (2008) https://doi.org/10.1117/12.779257

KEYWORDS: Radar, Detection and tracking algorithms, Transmitters, Receivers, Target detection, Doppler effect, Signal processing, Particles, FM band, Antennas

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Proceedings Article | 16 April 2008 Paper

Joint path planning and sensor subset selection for multistatic sensor networks

R. Tharmarasa, Tom Lang, T. Kirubarajan

Proceedings Volume 6969, 69690T (2008) https://doi.org/10.1117/12.779217

KEYWORDS: Sensors, Transmitters, Receivers, Sensor networks, Passive sensors, Genetic algorithms, Target detection, Detection and tracking algorithms, Neptunium, Surveillance

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Proceedings Article | 16 April 2008 Paper

Tracking with poorly localized sensors in multistatic sensor networks

R. Tharmarasa, T. Lang, T. Kirubarajan

Proceedings Volume 6969, 69690P (2008) https://doi.org/10.1117/12.779232

KEYWORDS: Sensors, Receivers, Sensor networks, Detection and tracking algorithms, Transmitters, Passive sensors, Global Positioning System, Computer simulations, Filtering (signal processing), Active sensors

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Proceedings Article | 25 September 2007 Paper

Spline filter for nonlinear/non-Gaussian Bayesian tracking

K. Punithakumar, T. Kirubarajan

Proceedings Volume 6699, 66990N (2007) https://doi.org/10.1117/12.734552

KEYWORDS: Nonlinear filtering, Particle filters, Particles, Detection and tracking algorithms, Digital filtering, Electronic filtering, Monte Carlo methods, Computer simulations, Filtering (signal processing), Numerical analysis

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Proceedings Article | 25 September 2007 Paper

Collaborative sensor management for decentralized asynchronous sensor networks

R. Tharmarasa, T. Kirubarajan

Proceedings Volume 6699, 66990Z (2007) https://doi.org/10.1117/12.734747

KEYWORDS: Sensors, Fluorescence correlation spectroscopy, Surveillance, Detection and tracking algorithms, Target detection, Active sensors, Particles, Sensor networks, Computer simulations, Telecommunications

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Proceedings Article | 25 September 2007 Paper

Improved multitarget tracking using probability hypothesis density smoothing

N. Nandakumaran, K. Punithakumar, T. Kirubarajan

Proceedings Volume 6699, 66990M (2007) https://doi.org/10.1117/12.734656

KEYWORDS: Nonlinear filtering, Detection and tracking algorithms, Digital filtering, Monte Carlo methods, Particles, Smoothing, Target detection, Computer simulations, Sensors, Optimal filtering

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Proceedings Article | 25 September 2007 Paper

Track-to-track association using informative prior associations

Daniel Danu, Abhijit Sinha, Thiagalingam Kirubarajan

Proceedings Volume 6699, 66990O (2007) https://doi.org/10.1117/12.732273

KEYWORDS: Sensors, Statistical analysis, Switching, Error analysis, Information fusion, Monte Carlo methods, Fourier transforms, Switches, Data processing, Astatine

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Proceedings Article | 25 September 2007 Paper

Computationally efficient assignment-based algorithms for data association for tracking with angle-only sensors

T. Sathyan, A. Sinha, T. Kirubarajan

Proceedings Volume 6699, 66990K (2007) https://doi.org/10.1117/12.734360

KEYWORDS: Sensors, Detection and tracking algorithms, Darmstadtium, Picosecond phenomena, Target detection, Computer simulations, Filtering (signal processing), Monte Carlo methods, Computing systems, Passive sensors

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In this paper we describe computationally efficient assignment-based algorithms to solve the data association problem in synchronous passive multisensor tracking systems. A traditional assignment-based solution to this problem is to solve the measurement-to-measurement association using multidimensional (S-dimensional or SD with S sensors) assignment formulation and the measurement-to-track association using two-dimensional assignment formulation. Even though this solution has been proven to be effective, it is computationally very expensive. One of the reasons is that in calculating the assignment cost of each possible candidate association one requires to find the maximum likelihood (ML) estimate of the unknown target state. The algorithms proposed in this paper use prior information of the targets that are being tracked to reduce the requirement for the costly ML estimation. The first algorithm is similar to the traditional two step technique except that it uses the predicted track information to avoid building the whole assignment tree in the measurement-to-measurement association. In particular, based on the predicted track information first validation gates are constructed for every target. Then, when forming the assignment tree, only the branches connecting measurements that satisfy the validation gate requirement are constructed. The second algorithm is a one-step algorithm in that it directly assigns the measurements to the tracks. We pose the data association problem as an (S + 1)-D assignment with the first dimension being the predicted state information of the tracks, and the rest of the S dimensions are the lists of measurements from the sensors. The costs of each possible (S + 1)-tuple are calculated based on the predicted track information, hence, the requirement for an ML estimate is eliminated. Further, we show that when the target maneuvers are not very high, and when the sensor measurements are uncorrelated the (S+1)-D assignment approximately decomposes into S individual 2-D assignments, resulting in huge computational savings.

Proceedings Article | 25 September 2007 Paper

Collaborative distributed sensor management for multitarget tracking using hierarchical Markov decision processes

D. Akselrod, A. Sinha, T. Kirubarajan

Proceedings Volume 6699, 669912 (2007) https://doi.org/10.1117/12.735173

KEYWORDS: Unmanned aerial vehicles, Sensors, Surveillance, Target detection, Radar, Detection and tracking algorithms, Monte Carlo methods, Stochastic processes, Chemical elements, Computer programming

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Proceedings Article | 25 September 2007 Paper

Improved observable operator model for joint target tracking and classification

S. Sutharsan, T. Kirubarajan

Proceedings Volume 6699, 66990U (2007) https://doi.org/10.1117/12.735322

KEYWORDS: Expectation maximization algorithms, Detection and tracking algorithms, Sensors, Systems modeling, Mathematical modeling, Computer simulations, Stochastic processes, Data modeling, Surveillance, Kinematics

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Proceedings Article | 25 September 2007 Paper

Hybrid radar signal fusion for unresolved target detection

N. Nandakumaran, A. Sinha, T. Kirubarajan

Proceedings Volume 6699, 669911 (2007) https://doi.org/10.1117/12.734513

KEYWORDS: Radar, Receivers, Target detection, Signal detection, Transmitters, Detection and tracking algorithms, Bismuth, Signal to noise ratio, Spatial resolution, Computer simulations

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Proceedings Article | 21 September 2007 Paper

Tracking dim targets using integrated clutter estimation

Edmund Brekke, Thiagalingam Kirubarajan, Ratnasingham Tharmarasa

Proceedings Volume 6699, 669905 (2007) https://doi.org/10.1117/12.734296

KEYWORDS: Signal to noise ratio, Particles, Sensors, Particle filters, Point spread functions, Detection and tracking algorithms, Clouds, Target detection, Monte Carlo methods, Digital filtering

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Proceedings Article | 16 May 2007 Paper

Invited panel discussion: Issues and challenges in uncertainty representation and management with applications to real-world problems

Ivan Kadar, Enrique Ruspini, Anne-Laure Jousselme, Patrick Maupin, Ronald Mahler, Joseph S. Peri, Pierre Valin, D. Akselrod, A. Sinha, T. Kirubarajan

Proceedings Volume 6567, 65670N (2007) https://doi.org/10.1117/12.741364

KEYWORDS: Probability theory, Data fusion, Sensors, Data modeling, Defense and security, Information fusion, Distributed computing, Chemical elements, Systems modeling, Fuzzy logic

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Proceedings Article | 7 May 2007 Paper

Two solutions to the localization using time difference of arrival problem

T. Sathyan, T. Kirubarajan

Proceedings Volume 6567, 656704 (2007) https://doi.org/10.1117/12.719068

KEYWORDS: Sensors, Monte Carlo methods, Chemical elements, Receivers, Global Positioning System, Unmanned aerial vehicles, Intelligence systems, Optimization (mathematics), MATLAB, Computer engineering

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Proceedings Article | 25 May 2006 Paper

Issues in resource management with applications to real-world problems

David Castañón, Ron Mahler, Kenneth Hintz, Jim Reich, Ivan Kadar, M. Farooq, T. Kirubarajan, R. Tharmarasa, T. Sathyan, A. Sinha

Proceedings Volume 6235, 62351O (2006) https://doi.org/10.1117/12.694899

KEYWORDS: Sensors, Data fusion, Sensor networks, Cameras, Sensing systems, Algorithm development, Computing systems, Detection and tracking algorithms, Information fusion, Error analysis

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Proceedings Article | 19 May 2006 Paper

Multitarget-multisensor management for decentralized sensor networks

R. Tharmarasa, T. Kirubarajan, A. Sinha, M. Hernandez

Proceedings Volume 6236, 62360W (2006) https://doi.org/10.1117/12.665793

KEYWORDS: Sensors, Fluorescence correlation spectroscopy, Surveillance, Detection and tracking algorithms, Sensor performance, Target detection, Time metrology, Computer simulations, Error analysis, Optimization (mathematics)

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Proceedings Article | 19 May 2006 Paper

Track quality based multitarget tracking algorithm

A. Sinha, Z. Ding, Thia Kirubarajan, M. Farooq

Proceedings Volume 6236, 623609 (2006) https://doi.org/10.1117/12.666319

KEYWORDS: Detection and tracking algorithms, Target detection, Quality measurement, Logic, Sensors, Personal digital assistants, Monte Carlo methods, Data modeling, Time metrology, Error analysis

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Proceedings Article | 19 May 2006 Paper

Collaborative sensor management for multitarget tracking using decentralized Markov decision processes

D. Akselrod, C. Goldman, A. Sinha, T. Kirubarajan

Proceedings Volume 6236, 623610 (2006) https://doi.org/10.1117/12.666357

KEYWORDS: Unmanned aerial vehicles, Sensors, Surveillance, Target detection, Detection and tracking algorithms, Monte Carlo methods, Radar, Stochastic processes, Chemical elements, Computer programming

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Proceedings Article | 19 May 2006 Paper

Weiss-Weinstein lower bound for maneuvering target tracking

T. Sathyan, M. Hernandez, A. Sinha, T. Kirubarajan

Proceedings Volume 6236, 62360G (2006) https://doi.org/10.1117/12.667792

KEYWORDS: Motion models, Matrices, Process modeling, Sensors, Switching, Astatine, Switches, Computer engineering, Detection and tracking algorithms, Radar

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Proceedings Article | 19 May 2006 Paper

Joint detection and tracking of unresolved targets with a joint-bin processing monopulse radar

N. Nandakumaran, A. Sinha, T. Kirubarajan

Proceedings Volume 6236, 62360T (2006) https://doi.org/10.1117/12.667648

KEYWORDS: Target detection, Radar, Detection and tracking algorithms, Particles, Bismuth, Magnesium, Monte Carlo methods, Particle filters, Algorithm development, Signal detection

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Proceedings Article | 17 May 2006 Paper

Autonomous search, tracking and classification by multiple cooperative UAVs

A. Sinha, T. Kirubarajan, Y. Bar-Shalom

Proceedings Volume 6235, 623508 (2006) https://doi.org/10.1117/12.668351

KEYWORDS: Unmanned aerial vehicles, Target detection, Sensors, Detection and tracking algorithms, Kinematics, Surveillance, Algorithm development, Objectives, Failure analysis, Synthetic aperture radar

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Proceedings Article | 17 May 2006 Paper

A distributed implementation of a sequential Monte Carlo probability hypothesis density filter for sensor networks

K. Punithakumar, T. Kirubarajan, A. Sinha

Proceedings Volume 6235, 62350L (2006) https://doi.org/10.1117/12.667772

KEYWORDS: Sensors, Detection and tracking algorithms, Monte Carlo methods, Sensor networks, Particle filters, Filtering (signal processing), Particles, Target detection, Complex systems, Nonlinear filtering

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Proceedings Article | 17 May 2006 Paper

Observable operator model-based joint target tracking and classification

S. Sutharsan, A. Sinha, T. Kirubarajan, M. Farooq

Proceedings Volume 6235, 623501 (2006) https://doi.org/10.1117/12.667793

KEYWORDS: Sensors, Expectation maximization algorithms, Detection and tracking algorithms, Mathematical modeling, Kinematics, Systems modeling, Stochastic processes, Feature extraction, Data integration, Algorithm development

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Proceedings Article | 10 May 2006 Paper

Intelligence-aided multitarget tracking for urban operations - a case study: counter terrorism

T. Sathyan, K. Bharadwaj, A. Sinha, T. Kirubarajan

Proceedings Volume 6201, 62010M (2006) https://doi.org/10.1117/12.669409

KEYWORDS: Roads, Kinematics, Detection and tracking algorithms, Strategic intelligence, Motion models, Surveillance, Buildings, Sensors, Chromium, Image segmentation

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Proceedings Article | 16 September 2005 Paper

An optimization-based parallel particle filter for multitarget tracking

S. Sutharsan, A. Sinha, T. Kirubarajan, M. Farooq

Proceedings Volume 5913, 591309 (2005) https://doi.org/10.1117/12.618456

KEYWORDS: Particles, Particle filters, Detection and tracking algorithms, Technetium, Algorithm development, Computer simulations, Surveillance, Computing systems, Computer architecture, Monte Carlo methods

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Proceedings Article | 16 September 2005 Paper

Data association in target tracking using priority queues

A. Sinha, T. Kirubarajan, M. Farooq

Proceedings Volume 5913, 59130P (2005) https://doi.org/10.1117/12.619175

KEYWORDS: Detection and tracking algorithms, Target detection, Algorithm development, Computer engineering, Chemical elements, Data fusion, Signal processing, Data processing, Binary data, MATLAB

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Proceedings Article | 16 September 2005 Paper

Joint detection and tracking of unresolved targets with a monopulse radar using a particle filter

N. Nandakumaran, A. Sinha, T. Kirubarajan

Proceedings Volume 5913, 59131T (2005) https://doi.org/10.1117/12.618441

KEYWORDS: Target detection, Radar, Particles, Bismuth, Monte Carlo methods, Algorithm development, Particle filters, Detection and tracking algorithms, Detector development, Signal processing

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Proceedings Article | 16 September 2005 Paper

Dynamic sensor management for distributed tracking

R. Tharmarasa, T. Kirubarajan, J. Peng

Proceedings Volume 5913, 59130Y (2005) https://doi.org/10.1117/12.618526

KEYWORDS: Sensors, Target detection, Detection and tracking algorithms, Platinum, Active sensors, Surveillance, Signal to noise ratio, Sensor performance, Computer simulations, Distributed computing

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Proceedings Article | 16 September 2005 Paper

Autonomous surveillance by multiple cooperative UAVs

A. Sinha, T. Kirubarajan, Y. Bar-Shalom

Proceedings Volume 5913, 59131V (2005) https://doi.org/10.1117/12.619266

KEYWORDS: Unmanned aerial vehicles, Target detection, Sensors, Detection and tracking algorithms, Surveillance, Algorithm development, Computer simulations, Radar, Failure analysis, Matrices

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Proceedings Article | 16 September 2005 Paper

A sequential Monte Carlo probability hypothesis density algorithm for multitarget track-before-detect

K. Punithakumar, T. Kirubarajan, A. Sinha

Proceedings Volume 5913, 59131S (2005) https://doi.org/10.1117/12.618438

KEYWORDS: Detection and tracking algorithms, Monte Carlo methods, Signal to noise ratio, Particles, Electronic filtering, Sensors, Digital filtering, Nonlinear filtering, Target detection, Algorithm development

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Proceedings Article | 25 May 2005 Paper

Performance evaluation of the randomized heuristic approach for multidimensional association

A. Sinha, T. Kirubarajan, M. Farooq

Proceedings Volume 5809, (2005) https://doi.org/10.1117/12.605462

KEYWORDS: Detection and tracking algorithms, Algorithm development, Filtering (signal processing), Computer engineering, Optimization (mathematics), Target recognition, Sensors, Chemical elements, Radar, Process modeling

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Proceedings Article | 25 May 2005 Paper

Passive geolocation and tracking of an unknown number of emitters

T. Sathyan, A. Sinha, T. Kirubarajan

Proceedings Volume 5809, (2005) https://doi.org/10.1117/12.601373

KEYWORDS: Sensors, Detection and tracking algorithms, Unmanned aerial vehicles, Darmstadtium, Monte Carlo methods, Surveillance, Algorithm development, Filtering (signal processing), Receivers, Target recognition

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Proceedings Article | 25 May 2005 Paper

A distributed multisensor-multitarget tracking testbed for maritime surveillance

D. Akselrod, A. Sinha, T. Kirubarajan, M. Farooq, Z. Ding

Proceedings Volume 5809, (2005) https://doi.org/10.1117/12.606780

KEYWORDS: Sensors, Data fusion, Detection and tracking algorithms, Environmental sensing, Data centers, Process modeling, Radar, Algorithm development, Surveillance, Kinematics

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Proceedings Article | 25 May 2005 Paper

Performance evaluation of nonlinear filters for tracking multiple ballistic targets

A. Sinha, N. Nandakumaran, S. Sutharsan, T. Kirubarajan, A El-Fallah, A. Zatezalo

Proceedings Volume 5809, (2005) https://doi.org/10.1117/12.606493

KEYWORDS: Particles, Particle filters, Detection and tracking algorithms, Electronic filtering, Nonlinear filtering, Filtering (signal processing), Monte Carlo methods, Target detection, Digital filtering, Complex systems

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Proceedings Article | 25 August 2004 Paper

A multiple-model probability hypothesis density filter for tracking maneuvering targets

Kumaradevan Punithakumar, Thiagalingam Kirubarajan, Abhijit Sinha

Proceedings Volume 5428, (2004) https://doi.org/10.1117/12.541885

KEYWORDS: Nonlinear filtering, Electronic filtering, Motion models, Target detection, Statistical modeling, Particles, Particle filters, Monte Carlo methods, Systems modeling, Performance modeling

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Proceedings Article | 25 August 2004 Paper

A convex minimization approach to data association with prior constraints

Huimin Chen, Thiagalingam Kirubarajan

Proceedings Volume 5428, (2004) https://doi.org/10.1117/12.540764

KEYWORDS: Feature selection, Detection and tracking algorithms, Computer programming

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Proceedings Article | 25 August 2004 Paper

Application of the Kalman-Levy filter for tracking maneuvering targets

Abhijit Sinha, Thiagalingam Kirubarajan, Yaakov Bar-Shalom

Proceedings Volume 5428, (2004) https://doi.org/10.1117/12.542896

KEYWORDS: Filtering (signal processing), Electronic filtering, Error analysis, Radar, Process modeling, Dynamical systems, Matrices, Detection and tracking algorithms, Motion models, Signal to noise ratio

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Proceedings Article | 25 August 2004 Paper

A randomized heuristic approach for multidimensional association in target tracking

Abhijit Sinha, Thiagalingam Kirubarajan

Proceedings Volume 5428, (2004) https://doi.org/10.1117/12.541894

KEYWORDS: Detection and tracking algorithms, Algorithm development, Robotics, Image processing, Optimization (mathematics), Computer simulations, Sensors, Radar, Process modeling, Monte Carlo methods

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Proceedings Article | 25 August 2004 Paper

Data association combined with the probability hypothesis density filter for multitarget tracking

Lin Lin, Yaakov Bar-Shalom, Thiagalingam Kirubarajan

Proceedings Volume 5428, (2004) https://doi.org/10.1117/12.542218

KEYWORDS: Particles, Detection and tracking algorithms, Electronic filtering, Particle filters, Automatic tracking, Computer simulations, Digital filtering, Sensors, Target detection, Electrochemical etching

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Proceedings Article | 25 August 2004 Paper

PCRLB-based multisensor array management for multitarget tracking

Ratnasingham Tharmarasa, Thiagalingam Kirubarajan, Marcel Hernandez

Proceedings Volume 5428, (2004) https://doi.org/10.1117/12.541884

KEYWORDS: Sensors, Target detection, Surveillance, Active sensors, Detection and tracking algorithms, Error analysis, Lead, Particle filters, Computer simulations, Numerical integration

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Proceedings Article | 9 August 2004 Paper

Geolocation of multiple emitters in the presence of clutter

Thuraiappah Sathyan, Thiagalingam Kirubarajan, Abhijit Sinha

Proceedings Volume 5429, (2004) https://doi.org/10.1117/12.542259

KEYWORDS: Sensors, Unmanned aerial vehicles, Motion models, Detection and tracking algorithms, Monte Carlo methods, Surveillance, Filtering (signal processing), Motion estimation, Electronic filtering, Electromagnetism

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Proceedings Article | 9 August 2004 Paper

Multisensor-multitarget bias estimation of asynchronous sensors

Xiangdong Lin, Yaakov Bar-Shalom, Thiagalingam Kirubarajan

Proceedings Volume 5429, (2004) https://doi.org/10.1117/12.542272

KEYWORDS: Sensors, Monte Carlo methods, Filtering (signal processing), Error analysis, Computer engineering, Sensor fusion, Detection and tracking algorithms, Signal processing, Systems modeling, Data communications

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Proceedings Article | 9 August 2004 Paper

Optimal cooperative placement of UAVs for ground target tracking with Doppler radar

Abhijit Sinha, Thiagalingam Kirubarajan, Yaakov Bar-Shalom

Proceedings Volume 5429, (2004) https://doi.org/10.1117/12.542903

KEYWORDS: Sensors, Target detection, Unmanned aerial vehicles, Radar, Detection and tracking algorithms, Doppler effect, Surveillance, Genetic algorithms, Knowledge management, Computer engineering

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Proceedings Article | 9 August 2004 Paper

Tracking spawning targets with a tagged particle filter

Abhijit Sinha, N. Nandakumaran, S. Sutharsan, Thiagalingam Kirubarajan

Proceedings Volume 5429, (2004) https://doi.org/10.1117/12.543353

KEYWORDS: Particles, Detection and tracking algorithms, Particle filters, Filtering (signal processing), Electronic filtering, Monte Carlo methods, Motion models, Target detection, Complex systems, Nonlinear filtering

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Proceedings Article | 5 January 2004 Paper

Adaptive sensor placement for target tracking in the presence of uncertainties

Kumaradevan Punithakumar, Thiagalingam Kirubarajan, Marcel Hernandez

Proceedings Volume 5204, (2004) https://doi.org/10.1117/12.504872

KEYWORDS: Sensors, Error analysis, Target detection, Unattended ground sensors, Motion models, Unmanned aerial vehicles, Submerged target detection, Warfare, Monte Carlo methods, Complex systems

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Proceedings Article | 5 January 2004 Paper

Large-scale optimal sensor array management for target tracking

Ratnasingham Tharmarasa, Thiagalingam Kirubarajan, Marcel Hernandez

Proceedings Volume 5204, (2004) https://doi.org/10.1117/12.504873

KEYWORDS: Sensors, Detection and tracking algorithms, Active sensors, Unattended ground sensors, Sensor performance, Time metrology, Error analysis, Laser induced plasma spectroscopy, Computer simulations, Particle filters

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Proceedings Article | 5 January 2004 Paper

Pursuer guidance parameter identification and time-to-go estimation using angle-only measurements from an evader

Lin Lin, Thiagalingam Kirubarajan, Yaakov Bar-Shalom

Proceedings Volume 5204, (2004) https://doi.org/10.1117/12.504567

KEYWORDS: Protactinium, Error analysis, Missiles, Monte Carlo methods, Mathematical modeling, Detection and tracking algorithms, Statistical analysis, Motion estimation, Motion models, Motion measurement

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Proceedings Article | 5 January 2004 Paper

Multisensor bias estimation using local tracks without a priori association

Xiangdong Lin, Thiagalingam Kirubarajan, Yaakov Bar-Shalom

Proceedings Volume 5204, (2004) https://doi.org/10.1117/12.503715

KEYWORDS: Sensors, Error analysis, Data analysis, Statistical analysis, Monte Carlo methods, Radar, Computer engineering, Data processing, Optical tracking, Computing systems

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Proceedings Article | 5 January 2004 Paper

Stochastic EM algorithm for nonlinear state estimation with model uncertainties

Amin Zia, Thiagalingam Kirubarajan, James Reilly, Shahram Shirani

Proceedings Volume 5204, (2004) https://doi.org/10.1117/12.506603

KEYWORDS: Expectation maximization algorithms, Detection and tracking algorithms, Particle filters, Data modeling, Monte Carlo methods, Particles, Stochastic processes, Process modeling, Algorithm development, Filtering (signal processing)

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In most solutions to state estimation problems like, for example, target tracking, it is generally assumed that the state evolution and measurement models are known a priori. The model parameters include process and measurement matrices or functions as well as the corresponding noise statistics. However, there are situations where the model parameters are not known a priori or are known only partially (i.e., with some uncertainty). Moreover, there are situations where the measurement is biased. In these scenarios, standard estimation algorithms like the Kalman ﬁlter and the extended Kalman Filter (EKF), which assume perfect knowledge of the model parameters, are not accurate. In this paper, the problem with uncertain model parameters is considered as a special case of maximum likelihood estimation with incomplete-data, for which a standard solution called the expectation-maximization (EM) algorithm exists. In this paper a new extension to the EM algorithm is proposed to solve the more general problem of joint state estimation and model parameter identiﬁcation for nonlinear systems with possibly non-Gaussian noise. In the expectation (E) step, it is shown that the best variational distribution over the state variables is the conditional posterior distribution of states given all the available measurements and inputs. Therefore, a particular type of particle filter is used to estimate and update the posterior distribution. In the maximization (M) step the nonlinear measurement process parameters are approximated using a nonlinear regression method for adjusting the parameters of a mixture of Gaussians (MofG). The proposed algorithm is used to solve a nonlinear bearing-only tracking problem similar to the one reported recently with uncertain measurement process. It is shown that the algorithm is capable of accurately tracking the state vector while identifying the unknown measurement dynamics. Simulation results show the advantages of the new technique over standard algorithms like the EKF whose performance degrades rapidly in the presence of uncertain models.

Proceedings Article | 5 January 2004 Paper

Tracking with classification-aided multiframe data association

Yaakov Bar-Shalom, Thiagalingam Kirubarajan, Cenk Gokberk

Proceedings Volume 5204, (2004) https://doi.org/10.1117/12.502405

KEYWORDS: Kinematics, Data processing, Detection and tracking algorithms, Sensors, Knowledge management, Electrochemical etching, Data integration, Electronic filtering, Binary data, Target detection

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In most conventional tracking systems, only the target kinematic information is used in measurement-to-track association. Target class information, which is typically used in postprocessing, can also be used to improve data association to give better tracking accuracy. In addition, the use of target class information in data association can improve discrimination by yielding purer tracks and preserve their continuity. In this paper, we present the integrated use of target classiﬁcation information and target kinematic information for target tracking. In our approach, target class information is integrated into the data association process using the two-dimensional (one track list and one measurement list) as well as multiframe (one track list and multiple measurement lists) assignments. The latter is an optimization based MHT. A generic model of the classifier output is considered and its use in association likelihoods is discussed. The multiframe association likelihood is developed to include the classification results based on the confusion matrix that speciﬁes the accuracy of the target classiﬁer. The objective is to improve association results using class information when the kinematic likelihoods are similar for different targets, i.e., there is ambiguity in using kinematic information alone. Performance comparison with and without the use of class information in data association is presented on a ground target tracking problem where targets are moving in an open field and their tracks can merge, branch and cross. Simulation results quantify the beneﬁts of classiﬁcation aided data association for improved target tracking, especially in the presence of association uncertainty in kinematic measurements. Also the beneﬁt of S-D (multiframe) association vs. 2-D association is investigated for different quality classiﬁers. The main contribution is the development of the methodology to incorporate exactly the classiﬁcation information into multidimensional (multiframe) association.

Proceedings Article | 5 January 2004 Paper

IMMPDAF solution for the tracking and radar management benchmark with merged measurements and multipath

Abhijit Sinha, Thiagalingam Kirubarajan, Yaakov Bar-Shalom

Proceedings Volume 5204, (2004) https://doi.org/10.1117/12.502895

KEYWORDS: Radar, Signal processing, Performance modeling, Detection and tracking algorithms, Target detection, Signal to noise ratio, Super resolution, Sensors, Radar signal processing, Data modeling

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Proceedings Article | 5 January 2004 Paper

EM-ML algorithm for track initialization with features using possibly noninformative data

Jie Cai, Thiagalingam Kirubarajan

Proceedings Volume 5204, (2004) https://doi.org/10.1117/12.503905

KEYWORDS: Expectation maximization algorithms, Detection and tracking algorithms, Signal to noise ratio, Target detection, Long wavelength infrared, Evolutionary algorithms, Surveillance, Artificial intelligence, Infrared radiation, Data modeling

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Initializing and maintaining a track for a low observable (low SNR, low target detection probability and high false alarm rate) target can be very challenging because of the low information content of measurements. In addition, in some scenarios, target-originated measurements might not be present in many consecutive scans because of mispointing, target maneuvers or erroneous preprocessing. That is, one might have a set of noninformative scans that could result in poor track initialization and maintenance. In this paper an algorithm based on the Expectation-Maximization (EM) algorithm combined with Maximum Likelihood (ML) estimation is presented for tracking slowly maneuvering targets in heavy clutter and possibly non-informative scans. The adaptive sliding-window EM-ML approach, which operates in batch mode, tries to reject or weight down non-informative scans using the Q-function in the M-step of the EM algorithm. A track validation technique is used to conﬁrm the validity of the EM-ML estimates. It is shown that target features in the form of, for example, amplitude information, can also be used to improve the estimates. In addition, performance bounds based on the supplemented EM (SEM) technique are also presented. The effectiveness of new algorithm is first demonstrated on a 78-frame Long Wave Infrared (LWIR) data sequence consisting of an F1 Mirage fighter jet in heavy clutter. Previously, this scenario has been used as a benchmark for evaluating the performance of other track initialization algorithms. The new EM-ML estimator conﬁrms the track by frame 20 while the ML-PDA (Maximum Likelihood estimator combined with Probabilistic Data Association) algorithm, the IMM-MHT (Interacting Multiple Model estimator combined with Multiple Hypothesis Tracking) and the IMM-PDA estimator previously required 28, 38 and 39 frames, respectively. The benefits of the new algorithm in terms of accuracy, early detection and computational load are illustrated using simulated scenarios as well.

Proceedings Article | 8 August 2003 Paper

Real-time diagnosis with sensors of uncertain quality

Ozgur Erdinc, Chaitra Raghavendra, Peter Willett, Thia Kirubarajan

Proceedings Volume 5107, (2003) https://doi.org/10.1117/12.486980

KEYWORDS: Sensors, Detection and tracking algorithms, Error analysis, Diagnostics, Systems modeling, Computer simulations, Algorithm development, Computing systems, System integration, Data modeling

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Proceedings Article | 7 August 2002 Paper

Comparison of EKF, pseudomeasurement, and particle filters for a bearing-only target tracking problem

Xiangdong Lin, Thiagalingam Kirubarajan, Yaakov Bar-Shalom, Simon Maskell

Proceedings Volume 4728, (2002) https://doi.org/10.1117/12.478508

KEYWORDS: Particle filters, Nonlinear filtering, Monte Carlo methods, Particles, Filtering (signal processing), Electronic filtering, Sensors, Error analysis, Surveillance, Linear filtering

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Proceedings Article | 7 August 2002 Paper

Maximum likelihood angle extractor in the presence of sea-surface multipath

Abhijit Sinha, W. Dale Blair, Thiagalingam Kirubarajan, Yaakov Bar-Shalom

Proceedings Volume 4728, (2002) https://doi.org/10.1117/12.478539

KEYWORDS: Radar, Reflection, Signal to noise ratio, Specular reflections, Error analysis, Signal processing, Detection and tracking algorithms, Silicon, Computer engineering, Analytical research

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Proceedings Article | 7 August 2002 Paper

MDL approach for multiple low-observable track initiation

Huimin Chen, Thiagalingam Kirubarajan, Yaakov Bar-Shalom, Krishna Pattipati

Proceedings Volume 4728, (2002) https://doi.org/10.1117/12.478528

KEYWORDS: Radar, Signal to noise ratio, Missiles, Target detection, Data modeling, Target acquisition, Composites, Detection and tracking algorithms, Data analysis, Performance modeling

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Proceedings Article | 7 August 2002 Paper

Efficient multisensor resource management using Cramer-Rao lower bounds

Marcel Hernandez, Thiagalingam Kirubarajan, Yaakov Bar-Shalom

Proceedings Volume 4728, (2002) https://doi.org/10.1117/12.478520

KEYWORDS: Sensors, Error analysis, Detection and tracking algorithms, Particle filters, Process control, Target detection, Monte Carlo methods, Submerged target modeling, Matrices, Warfare

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Proceedings Article | 7 August 2002 Paper

Efficient particle filters for joint tracking and classification

Neil Gordon, Simon Maskell, Thiagalingam Kirubarajan

Proceedings Volume 4728, (2002) https://doi.org/10.1117/12.478524

KEYWORDS: Particle filters, Particles, Detection and tracking algorithms, Sensors, Radar, Filtering (signal processing), Kinematics, Monte Carlo methods, Systems modeling, FDA class I medical device development

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Proceedings Article | 16 July 2002 Paper

Useful lifetime tracking via the IMM

Ethan Phelps, Peter Willett, Thiagalingam Kirubarajan

Proceedings Volume 4733, (2002) https://doi.org/10.1117/12.475504

KEYWORDS: Sensors, Failure analysis, Filtering (signal processing), Motion models, Binary data, Kinematics, Systems modeling, Signal processing, Detection and tracking algorithms, Autoregressive models

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Proceedings Article | 26 November 2001 Paper

3D track initiation in clutter using 2D measurements

Lin Lin, Thiagalingam Kirubarajan, Yaakov Bar-Shalom

Proceedings Volume 4473, (2001) https://doi.org/10.1117/12.492763

KEYWORDS: Sensors, Radar, 3D metrology, Motion estimation, Monte Carlo methods, Detection and tracking algorithms, 3D acquisition, Personal digital assistants, Surveillance, Error analysis

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Proceedings Article | 26 November 2001 Paper

Enhanced-accuracy GPS navigation using the interacting multiple-model estimator

Xiangdong Lin, Thiagalingam Kirubarajan, Yaakov Bar-Shalom, X. Rong Li

Proceedings Volume 4473, (2001) https://doi.org/10.1117/12.492767

KEYWORDS: Motion models, Global Positioning System, Satellites, Error analysis, Motion estimation, Navigation systems, Clocks, Receivers, Filtering (signal processing), Monte Carlo methods

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Proceedings Article | 20 July 2001 Paper

Statistical approach to prognostics

Ethan Phelps, Peter Willett, Thiagalingam Kirubarajan

Proceedings Volume 4389, (2001) https://doi.org/10.1117/12.434249

KEYWORDS: Systems modeling, Failure analysis, Sensors, Filtering (signal processing), Binary data, Signal processing, Computing systems, Diagnostics, Electronic filtering, Data archive systems

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Proceedings Article | 20 July 2001 Paper

Capacity and reliability analyses with applications to power quality

Mohammad Azam, Fang Tu, Yuri Shlapak, Thiagalingam Kirubarajan, Krishna Pattipati, Rajaiah Karanam

Proceedings Volume 4389, (2001) https://doi.org/10.1117/12.434255

KEYWORDS: Computing systems, Reliability, Data centers, Evolutionary algorithms, Telecommunications, Power supplies, Transformers, Failure analysis, Software development, Data modeling

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Proceedings Article | 20 July 2001 Paper

Sequential Monte Carlo filtering vs. the IMM estimator for fault detection and isolation in nonlinear systems

Visakan Kadirkamanathan, P. Li, Thiagalingam Kirubarajan

Proceedings Volume 4389, (2001) https://doi.org/10.1117/12.434246

KEYWORDS: Monte Carlo methods, Particles, Complex systems, Failure analysis, Nonlinear filtering, Filtering (signal processing), Particle filters, Systems modeling, Electronic filtering, Dynamical systems

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Proceedings Article | 20 July 2001 Paper

Fault detection algorithms for real-time diagnosis in large-scale systems

Thiagalingam Kirubarajan, Venkatesh Malepati, Somnath Deb, Jie Ying

Proceedings Volume 4389, (2001) https://doi.org/10.1117/12.434244

KEYWORDS: Associative arrays, Analytical research, Computer simulations, Diagnostics, Sensors, Detection and tracking algorithms, Computing systems, Systems modeling, Reliability, Data modeling

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Proceedings Article | 13 July 2000 Paper

Tracking evasive move-stop-move targets with a MTI radar using a VS-IMM estimator

Thiagalingam Kirubarajan, Yaakov Bar-Shalom

Proceedings Volume 4048, (2000) https://doi.org/10.1117/12.391980

KEYWORDS: Target detection, Motion models, Motion estimation, Sensors, Error analysis, Motion measurement, Radar, Filtering (signal processing), Signal processing, Digital filtering

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Proceedings Article | 13 July 2000 Paper

Signal processing, tracking, and resource allocation for highly maneuvering closely spaced targets

Abhijit Sinha, Thiagalingam Kirubarajan, Yaakov Bar-Shalom

Proceedings Volume 4048, (2000) https://doi.org/10.1117/12.392009

KEYWORDS: Radar, Signal processing, Detection and tracking algorithms, Target detection, Signal to noise ratio, Monte Carlo methods, Antennas, Radar signal processing, Computer simulations, Data modeling

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Proceedings Article | 13 July 2000 Paper

Kalman filter vs. IMM estimator: when do we need the latter?

Thiagalingam Kirubarajan, Yaakov Bar-Shalom

Proceedings Volume 4048, (2000) https://doi.org/10.1117/12.392013

KEYWORDS: Filtering (signal processing), Error analysis, Motion estimation, Performance modeling, Motion models, Motion measurement, Sensors, Process modeling, Electronic filtering, Detection and tracking algorithms

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Proceedings Article | 13 July 2000 Paper

Adaptive early detection ML/PDA estimator for LO targets with EO sensors

Muhammad Chummun, Thiagalingam Kirubarajan, Yaakov Bar-Shalom

Proceedings Volume 4048, (2000) https://doi.org/10.1117/12.391991

KEYWORDS: Target detection, Signal to noise ratio, Detection and tracking algorithms, Sensors, Surveillance, Signal detection, Electro optical sensors, Signal processing, Aluminum, Electro optics

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Proceedings Article | 13 July 2000 Paper

Comparison of centralized and distributed tracking algorithms using air-to-air scenarios

Huimin Chen, Thiagalingam Kirubarajan, Yaakov Bar-Shalom

Proceedings Volume 4048, (2000) https://doi.org/10.1117/12.391997

KEYWORDS: Filtering (signal processing), Polonium, Error analysis, Sensors, Motion models, Detection and tracking algorithms, Electronic filtering, Radar, Motion estimation, Performance modeling

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Proceedings Article | 3 September 1998 Paper

Ground-target tracking with topography-based variable-structure IMM estimator

Thiagalingam Kirubarajan, Yaakov Bar-Shalom, Krishna Pattipati, Ivan Kadar

Proceedings Volume 3373, (1998) https://doi.org/10.1117/12.324622

KEYWORDS: Roads, Motion models, Motion estimation, Detection and tracking algorithms, Sensors, Error analysis, Data modeling, Visibility, Process modeling, Target detection

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Proceedings Article | 17 July 1998 Paper

Efficient multisensor fusion using multidimensional assignment for multitarget tracking

Thiagalingam Kirubarajan, Hao Wang, Yaakov Bar-Shalom, Krishna Pattipati

Proceedings Volume 3374, (1998) https://doi.org/10.1117/12.327101

KEYWORDS: Sensors, Detection and tracking algorithms, Data fusion, Automatic tracking, Surveillance, Radar, Sensor fusion, Statistical analysis, Algorithm development, Sensor performance

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Proceedings Article | 29 October 1997 Paper

Large-scale air traffic surveillance using an IMM estimator with assignment

Hui Wang, Thiagalingam Kirubarajan, Yicong Li, Yaakov Bar-Shalom

Proceedings Volume 3163, (1997) https://doi.org/10.1117/12.283965

KEYWORDS: Sensors, Motion models, Detection and tracking algorithms, Radar, Skin, Target detection, Surveillance, Data modeling, Filtering (signal processing), Error analysis

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Proceedings Article | 29 October 1997 Paper

Multiassignment for tracking a large number of overlapping objects

Thiagalingam Kirubarajan, Yaakov Bar-Shalom, Krishna Pattipati

Proceedings Volume 3163, (1997) https://doi.org/10.1117/12.283967

KEYWORDS: Detection and tracking algorithms, Image segmentation, Target detection, Personal digital assistants, Optical resolution, Algorithm development, Eye, Image processing algorithms and systems, Tissues, Biomedical optics

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Proceedings Article | 31 May 1996 Paper

Comparison of IMMPDA and IMM-assignment algorithms on real air traffic surveillance data

Thiagalingam Kirubarajan, Murali Yeddanapudi, Yaakov Bar-Shalom, Krishna Pattipati

Proceedings Volume 2759, (1996) https://doi.org/10.1117/12.241206

KEYWORDS: Detection and tracking algorithms, Data modeling, Motion models, Target detection, Error analysis, Surveillance, Filtering (signal processing), Tumor growth modeling, Sensors, Motion estimation

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Showing 5 of 123 publications

Proceedings Volume Editor (12)

SPIE Conference Volume | 20 July 2023

Signal Processing, Sensor/Information Fusion, and Target Recognition XXXII

SPIE Conference Volume | 6 July 2022

Signal Processing, Sensor/Information Fusion, and Target Recognition XXXI

SPIE Conference Volume | 24 May 2021

Signal Processing, Sensor/Information Fusion, and Target Recognition XXX

SPIE Conference Volume | 5 June 2020

Signal Processing, Sensor/Information Fusion, and Target Recognition XXIX

SPIE Conference Volume | 22 August 2019

Signal Processing, Sensor/Information Fusion, and Target Recognition XXVIII

Showing 5 of 12 publications

Conference Committee Involvement (24)

Signal Processing, Sensor/Information Fusion, and Target Recognition XXXIII

22 April 2024 | National Harbor, Maryland, United States

Signal Processing, Sensor/Information Fusion, and Target Recognition XXXII

1 May 2023 | Orlando, Florida, United States

Signal Processing, Sensor/Information Fusion, and Target Recognition XXXI

4 April 2022 | Orlando, Florida, United States

Signal Processing, Sensor/Information Fusion, and Target Recognition XXX

12 April 2021 | Online Only, Florida, United States

Signal Processing, Sensor/Information Fusion, and Target Recognition XXIX

27 April 2020 | Online Only, California, United States

Signal Processing, Sensor/Information Fusion, and Target Recognition XXVIII

15 April 2019 | Baltimore, MD, United States

Signal Processing, Sensor/Information Fusion, and Target Recognition XXVII

16 April 2018 | Orlando, FL, United States

Signal Processing, Sensor/Information Fusion, and Target Recognition XXVI

10 April 2017 | Anaheim, CA, United States

Signal Processing, Sensor/Information Fusion, and Target Recognition XXV

18 April 2016 | Baltimore, MD, United States

Signal Processing, Sensor/Information Fusion, and Target Recognition XXIV

20 April 2015 | Baltimore, MD, United States

Signal Processing, Sensor/Information Fusion, and Target Recognition XXIII

5 May 2014 | Baltimore, MD, United States

Signal Processing, Sensor Fusion, and Target Recognition XXII

29 April 2013 | Baltimore, Maryland, United States

Signal Processing, Sensor Fusion, and Target Recognition XXI

23 April 2012 | Baltimore, Maryland, United States

Signal Processing, Sensor Fusion, and Target Recognition XX

25 April 2011 | Orlando, Florida, United States

Signal Processing, Sensor Fusion, and Target Recognition XIX

5 April 2010 | Orlando, Florida, United States

Signal Processing, Sensor Fusion, and Target Recognition XVIII

13 April 2009 | Orlando, Florida, United States

Signal Processing, Sensor Fusion, and Target Recognition XVII

17 March 2008 | Orlando, Florida, United States

Signal Processing, Sensor Fusion, and Target Recognition XVI

9 April 2007 | Orlando, Florida, United States

Signal Processing, Sensor Fusion, and Target Recognition XV

17 April 2006 | Orlando (Kissimmee), Florida, United States

Signal Processing, Sensor Fusion, and Target Recognition XIV

28 March 2005 | Orlando, Florida, United States

Signal Processing, Sensor Fusion, and Target Recognition XIII

12 April 2004 | Orlando, Florida, United States

System Diagnosis and Prognosis: Security and Condition Monitoring Issues III

21 April 2003 | Orlando, Florida, United States

Component and Systems Diagnostics, Prognostics, and Health Management II

3 April 2002 | Orlando, FL, United States

Component and Systems Diagnostics, Prognosis, and Health Management

16 April 2001 | Orlando, FL, United States

Showing 5 of 24 Conference Committees

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