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Proceedings Paper

Tracking low SNR targets using particle filter with flow control
Author(s): Nima Moshtagh; Paul M. Romberg; Moses W. Chan
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Paper Abstract

In this work we study the problem of detecting and tracking challenging targets that exhibit low signal-to-noise ratios (SNR). We have developed a particle filter-based track-before-detect (TBD) algorithm for tracking such dim targets. The approach incorporates the most recent state estimates to control the particle flow accounting for target dynamics. The flow control enables accumulation of signal information over time to compensate for target motion. The performance of this approach is evaluated using a sensitivity analysis based on varying target speed and SNR values. This analysis was conducted using high-fidelity sensor and target modeling in realistic scenarios. Our results show that the proposed TBD algorithm is capable of tracking targets in cluttered images with SNR values much less than one.

Paper Details

Date Published: 13 June 2014
PDF: 11 pages
Proc. SPIE 9092, Signal and Data Processing of Small Targets 2014, 90920A (13 June 2014); doi: 10.1117/12.2050523
Show Author Affiliations
Nima Moshtagh, Lockheed Martin Space Systems Co. (United States)
Paul M. Romberg, Lockheed Martin Space Systems Co. (United States)
Moses W. Chan, Lockheed Martin Space Systems Co. (United States)


Published in SPIE Proceedings Vol. 9092:
Signal and Data Processing of Small Targets 2014
Oliver E. Drummond, Editor(s)

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