Assessment of a Bayesian approach to recognising relocatable targets
Richard O. Lane, Keith D. Copsey, Andrew R. Webb · 2005
This paper considers an automatic target recognition concept in which a long-range targeting sensor is used to aid a radar seeker-equipped weapon operating in an area containing high-value relocatable targets. The weapon seeker is designed to engage the high-value targets, while minimising collateral damage. Previous work proposed a Bayesian approach that enables the weapon seeker to exploit the targeting information before making its nal decision. The approach matches the scenes in the seeker domain with those from the targeting sensor, while taking into account uncertainty and data latency. The proposed solution utilises a Bayesian technique known as particle ltering, and had previously only been applied to a synthetic example. This paper summarises the approach, and presents results from an assessment using scenarios derived from an airborne data set containing short-range Doppler beam sharpened imagery. The issue of diering resolutions for the two sensors is addressed by super-resolution techniques, which are also assessed.