17 May 2012 Consistency of stochastic context-free grammars and application to stochastic parsing of GMTI tracker data
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Abstract
Conventional trackers provide the human operator with estimated target tracks. It is desirable to make higher level inference of the target behaviour/intent (e.g., trajectory inference) in an automated manner. One such approach is to use stochastic context-free grammars and the Earley-Stoelcke parsing algorithm. The problem of inference is reformulated as one of parsing. In this paper, the consistency of stochastic context-free grammars is reviewed. Some examples illustrating the constraints on SCFGs due to consistency are presented, including a toy SCFG that has been used to successfully parse real GMTI radar data.
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Bhashyam Balaji, "Consistency of stochastic context-free grammars and application to stochastic parsing of GMTI tracker data", Proc. SPIE 8392, Signal Processing, Sensor Fusion, and Target Recognition XXI, 83920S (17 May 2012); doi: 10.1117/12.921155; https://doi.org/10.1117/12.921155
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