Particle Filtering in High Clutter Environment
نویسندگان
چکیده
This paper addresses the effect of clutter in direction of arrival (DOA) tracking from a passive acoustic sensor station. DOA signal is characterized by non-linearities arising from the measurement model. Strong dynamics combined with signal deterioration such as clutter can cause filters to diverge. A family of Monte Carlo methods known as particle filters has been used in variety of problems dealing with non-linear models and non-Gaussian distributions. In this paper a filter based on Sampling Importance Resampling (SIR) is used to track DOA within high clutter environment. Description of the filtering algorithm is presented and experiments are carried out with DOA estimate sequences generated from a simulated scenario. Performance of the filter is tested against different amounts of noise, both additive and one rising from clutter. Result indicate a decrease in filter performance with high amounts of clutter and strong target movement.
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