A spawning particle filter for defocused moving target detection in GNSS-based passive radar

Global Navigation Satellite System(GNSS)-based passive radar(GBPR) has been widely used in remote sensing applications. However, for moving target detection(MTD), the quadratic phase error(QPE) introduced by the non-cooperative target motion is usually difficult to be compensated, as the low power level of the GBPR echo signal renders the estimation of the Doppler rate less effective. Consequently, the moving target in GBPR image is usually defocused, which aggravates the difficulty of target detection even further. In this paper, a spawning particle filter(SPF) is proposed for defocused MTD. Firstly, the measurement model and the likelihood ratio function(LRF) of the defocused point-like target image are deduced. Then, a spawning particle set is generated for subsequent target detection,with reference to traditional particles in particle filter(PF) as their parent. After that, based on the PF estimator, the SPF algorithm and its sequential Monte Carlo(SMC) implementation are proposed with a novel amplitude estimation method to decrease the target state dimension. Finally, the effectiveness of the proposed SPF is demonstrated by numerical simulations and preliminary experimental results, showing that the target range and Doppler can be estimated accurately.