Intent Inference and Syntactic Tracking with GMTI Measurements

Alex Wang; Vikram Krishnamurthy; Bhashyam Balaji

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arXiv · 1104.4376

Intent Inference and Syntactic Tracking with GMTI Measurements

Alex Wang·Vikram Krishnamurthy·Bhashyam Balaji

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Abstract

In conventional target tracking systems, human operators use the estimated target tracks to make higher level inference of the target behaviour/intent. This paper develops syntactic filtering algorithms that assist human operators by extracting spatial patterns from target tracks to identify suspicious/anomalous spatial trajectories. The targets' spatial trajectories are modeled by a stochastic context free grammar (SCFG) and a switched mode state space model. Bayesian filtering algorithms for stochastic context free grammars are presented for extracting the syntactic structure and illustrated for a ground moving target indicator (GMTI) radar example. The performance of the algorithms is tested with the experimental data collected using DRDC Ottawa's X-band Wideband Experimental Airborne Radar (XWEAR).

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Alex Wang, Vikram Krishnamurthy, Bhashyam Balaji. 2011-04-22. Intent Inference and Syntactic Tracking with GMTI Measurements. https://arxiv.org/abs/1104.4376

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