%0 Journal Article
%T A Bayesian track-before-detect procedure for passive radars
%A Khalil Jishy and Frederic Lehmann
%J EURASIP Journal on Advances in Signal Processing
%D 2013
%I 
%R 10.1186/1687-6180-2013-45
%X This article presents a Bayesian algorithm for detection and tracking of a target using the track-before-detect framework. This strategy enables to detect weak targets and to circumvent the data association problem originating from the detection stage of classical radar systems. We first establish a Bayesian recursion, which propagates the target state probability density function. Since raw measurements are generally related to the target state through a nonlinear observation function, this recursion does not admit a closed form expression. Therefore, in order to obtain a tractable formulation, we propose a Gaussian mixture approximation. Our targeted application is passive radar, with civilian broadcasters used as illuminators of opportunity. Numerical simulations show the ability of the proposed algorithm to detect and track a target at very low signal-to-noise ratios.
%U http://asp.eurasipjournals.com/content/2013/1/45/abstract