Share Email Print

Proceedings Paper

Boosting target tracking using particle filter with flow control
Format Member Price Non-Member Price
PDF $17.00 $21.00

Paper Abstract

Target detection and tracking with passive infrared (IR) sensors can be challenging due to significant degradation and corruption of target signature by atmospheric transmission and clutter effects. This paper summarizes our efforts in phenomenology modeling of boosting targets with IR sensors, and developing algorithms for tracking targets in the presence of background clutter. On the phenomenology modeling side, the clutter images are generated using a high fidelity end-to-end simulation testbed. It models atmospheric transmission, structured clutter and solar reflections to create realistic background images. The dynamics and intensity of a boosting target are modeled and injected onto the background scene. Pixel level images are then generated with respect to the sensor characteristics. On the tracking analysis side, a particle filter for tracking targets in a sequence of clutter images is developed. The particle filter is augmented with a mechanism to control particle flow. Specifically, velocity feedback is used to constrain and control the particles. The performance of the developed “adaptive” particle filter is verified with tracking of a boosting target in the presence of clutter and occlusion.

Paper Details

Date Published: 20 May 2013
PDF: 15 pages
Proc. SPIE 8744, Automatic Target Recognition XXIII, 87440I (20 May 2013); doi: 10.1117/12.2015444
Show Author Affiliations
Nima Moshtagh, Lockheed Martin Space Systems Co. (United States)
Moses W. Chan, Lockheed Martin Space Systems Co. (United States)

Published in SPIE Proceedings Vol. 8744:
Automatic Target Recognition XXIII
Firooz A. Sadjadi; Abhijit Mahalanobis, Editor(s)

© SPIE. Terms of Use
Back to Top
Sign in to read the full article
Create a free SPIE account to get access to
premium articles and original research
Forgot your username?