Mr. Charles A. Bjork Profile

Charles A. Bjork

Retired

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Publications (6)

Proceedings Article | 4 May 2010 Paper

Mid-wave infrared (MWIR) panoramic sensor for various applications

Charles Bjork, William Wan

Proceedings Volume 7660, 76600B (2010) https://doi.org/10.1117/12.849348

KEYWORDS: Sensors, Panoramic photography, Signal to noise ratio, Mid-IR, Infrared sensors, Staring arrays, Sensor performance, Interfaces, Commercial off the shelf technology, Image sensors

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Proceedings Article | 20 October 2004 Paper

Angle-discrimination-based pointing and tracking for free-space communication links

Narasimha Prasad, Patrick Kratovil, Charles Bjork, Neil Vallestero

Proceedings Volume 5550, (2004) https://doi.org/10.1117/12.562084

KEYWORDS: Receivers, Sensors, Transmitters, Scintillation, Scanners, Modulation, Telecommunications, Transponders, Data acquisition, Global Positioning System

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Proceedings Article | 12 March 1999 Paper

Sensor fusion options for ballistic missile defense interceptor applications

Charles Bjork, Norman Morris, Belur Dasarathy, Bart Smith, Doug Allen, William Prestwood

Proceedings Volume 3719, (1999) https://doi.org/10.1117/12.341332

KEYWORDS: Sensors, LIDAR, Missiles, Defense and security, Data acquisition, Sensor fusion, Data fusion, Infrared sensors, Fuzzy logic, Logic

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Proceedings Article | 3 September 1998 Paper

Assessment of aimpoint selection performance utilizing feature selection algorithms and the signal processing environment for analysis and reduction (SPEAR)

Charles Bjork, G. Blake, Beverly Stark-Kublin, John Rushing

Proceedings Volume 3373, (1998) https://doi.org/10.1117/12.324614

KEYWORDS: LIDAR, Sensors, Feature selection, Doppler effect, Speckle, Signal processing, Detection and tracking algorithms, Image resolution, Feature extraction, Error analysis

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Proceedings Article | 20 March 1998 Paper

Intelligent processing techniques for sensor fusion

Katherine Byrd, Bart Smith, Doug Allen, Norman Morris, Charles Bjork, Kim Deal-Giblin, John Rushing

Proceedings Volume 3376, (1998) https://doi.org/10.1117/12.303669

KEYWORDS: Sensors, LIDAR, Intelligent sensors, Algorithm development, Target designation, Detection and tracking algorithms, Signal to noise ratio, Sensor fusion, Infrared sensors, Feature extraction

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Intelligent processing techniques which can effectively combine sensor data from disparate sensors by selecting and using only the most beneficial individual sensor data is a critical element of exoatmospheric interceptor systems. A major goal of these algorithms is to provide robust discrimination against stressing threats in poor a priori conditions, and to incorporate adaptive approaches in off- nominal conditions. This paper summarizes the intelligent processing algorithms being developed, implemented and tested to intelligently fuse data from passive infrared and active LADAR sensors at the measurement, feature and decision level. These intelligent algorithms employ dynamic selection of individual sensors features and the weighting of multiple classifier decisions to optimize performance in good a priori conditions and robustness in poor a priori conditions. Features can be dynamically selected based on an estimate of the feature confidence which is determined from feature quality and weighting terms derived from the quality of sensor data and expected phenomenology. Multiple classifiers are employed which use both fuzzy logic and knowledge based approaches to fuse the sensor data and to provide a target lethality estimate. Target designation decisions can be made by fusing weighted individual classifier decisions whose output contains an estimate of the confidence of the data and the discrimination decisions. The confidence in the data and decisions can be used in real time to dynamically select different sensor feature data or to request additional sensor data on specific objects that have not been confidently identified as being lethal or non- lethal. The algorithms are implemented in C within a graphic user interface framework. Dynamic memory allocation and the sequentialy implementation of the feature algorithms are employed. The baseline set of fused sensor discrimination algorithms with intelligent processing are described in this paper. Example results from the algorithms are shown based on static range sensor measurement data.

Proceedings Article | 16 June 1997 Paper

Intelligent fusion processing in BMD applications

Claire McCullough, Katherine Byrd, Charles Bjork, Gary Grider, Bart Smith, Norman Morris, Belur Dasarathy

Proceedings Volume 3067, (1997) https://doi.org/10.1117/12.276118

KEYWORDS: Sensors, LIDAR, Intelligent sensors, Neural networks, Data fusion, Doppler effect, Computer simulations, Detection and tracking algorithms, Infrared sensors, Infrared signatures

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Showing 5 of 6 publications

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