Modeling intent for a target tracking and identification scenario

Erik P. Blasch

doi:10.1117/12.542897

25 August 2004 Modeling intent for a target tracking and identification scenario

Erik P. Blasch

Proceedings Volume 5428, Signal and Data Processing of Small Targets 2004; (2004) https://doi.org/10.1117/12.542897
Event: Defense and Security, 2004, Orlando, Florida, United States

Abstract

The tracking goal is to reduce positional uncertainty. There are many ways to reduce tracking uncertainty: including classification data, using trafficability maps, and employing behavior information. We seek to extend tracking and identification modeling by incorporating intent to update prediction velocity vectors. A hybrid state space approach is formulated to deal with continuous-valued kinematics and discrete-valued target type, pose (inherently continuous but quantized), and intent behavior. The coupled tracker design is illustrated within the context of using ground moving target indicator (GMTI) and high range-resolution (HRRR) measurements as well as digital terrain elevation data (DTED), road map, and estimated goal states. The resulting Intent Coupled Tracking and Identification (ICTI) system is expected to outperform separately designed systems particularly during target maneuvers and recovering from temporary data dropout.

Citation Download Citation

Erik P. Blasch "Modeling intent for a target tracking and identification scenario", Proc. SPIE 5428, Signal and Data Processing of Small Targets 2004, (25 August 2004); https://doi.org/10.1117/12.542897

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available