Tracking a maneuvering target in the presence of clutter by multiple detection radar and infrared sensor

In this paper, an algorithm is proposed for tracking a highly maneuvering target in the presence of clutter by fusion of multiple detection radar and infrared sensor. It is presented by combining interactive multiple model (IMM) and multiple detection probabilistic data association filter (MDPDAF) in a multi-sensor (radar and infrared) scenario known as IMM/MS-MDPDAF algorithm. Multiple radar detection could be due to multipath or extended nature of the target such that in each scan there would be more than one valid target detection. In the presence of multiple radar detection there is uncertainty in data association in addition to the measurements origin (target or false alarm), in the number of measurements arising from the target. Accordingly MDPDAF algorithm that considers both uncertainties is developed instead of the standard PDAF algorithm which only considers the uncertainty in the measurements origin. The simulation has shown that in the presence of multiple radar detection, tracking with the proposed algorithm that considers both uncertainties has considerable improvement compared to the IMM/MSPDAF algorithm that only considers uncertainty in the measurements origin.