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Proceedings Paper

Tracking move-stop-move targets with state-dependent mode transition probabilities
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Paper Abstract

This paper presents a novel method for tracking ground moving targets with a GMTI radar. To avoid detection by the GMTI radar, targets can deliberately stop for some time before moving again. The GMTI radar does not detect a target when the radial velocity (along the line-of-sight from the sensor) falls below a certain minimum detectable velocity (MDV). We develop a new approach by using state-dependent mode transition probabilities to track move-stop-move targets. Since in a real scenario, the maximum deceleration is always limited, a target can not switch to the stopped-target model from a high speed. Therefore, with the use of the stopped-target model, the Markov chain of the mode switching has jump probabilities that depend on the target's kinematic state. A mode transition matrix with zero jump probabilities to the stopped-target mode is used when the speed is above a certain "stopping" limit (above which the target cannot stop in one sampling interval, designated as "fast stage") and another transition matrix with non-zero jump probabilities to the stopped-target mode is used when the speed is below this limit (designated as "slow stage"). The stage probabilities are calculated using the kinematic state statistics from the IMM estimator and then used to combine the state-dependent mode transition probabilities (SDP) in the two different transition matrices. The experimental results show that the proposed algorithm outperforms previous methods.

Paper Details

Date Published: 4 September 2009
PDF: 12 pages
Proc. SPIE 7445, Signal and Data Processing of Small Targets 2009, 74450L (4 September 2009); doi: 10.1117/12.832316
Show Author Affiliations
Shuo Zhang, Univ. of Connecticut (United States)
Yaakov Bar-Shalom, Univ. of Connecticut (United States)

Published in SPIE Proceedings Vol. 7445:
Signal and Data Processing of Small Targets 2009
Oliver E. Drummond; Richard D. Teichgraeber, Editor(s)

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