Towards an online, adaptive algorithm for radar surveillance control

Multifunction radars are highly configurable and possess some form of beam agility, allowing maintenance of a large number of tasks supporting varied functions. However, the surveillance function is commonly executed using a fixed periodic pattern, not utilising the full hardware potential. In this paper, a new method of surveillance control is proposed which utilises a particle filter to estimate a probability density of the undetected target location. Subsequently, the finite resource available for surveillance is allocated between sectors, based on information extracted from this probability density, using the Continuous Double Auction Parameter Selection algorithm. This method is successfully demonstrated through simulation on a surveillance control problem.