Recursive Bayesian Filtering for Multitarget Track-Before-Detect in Passive Radars
Frédéric François Lehmann · IEEE Transactions on Aerospace and Electronic Systems · 2012
This paper presents a Bayesian algorithm for joint detection and tracking in a multitarget setting. Raw measurements are processed using the track-before-detect (TBD) framework. We first establish a Bayesian recursion, which propagates a probability of target existence along with a target state probability density per delay/Doppler bin. In order to handle the nonlinearity of the observation model obtained for orthogonal frequency division multiplexing (OFDM)-based passive radar, a suitable Gaussian mixture implementation is proposed.