CS–MMPF‐based weak target detection and tracking with range ambiguity

Abstract

To address the problem of target detection and tracking with the range ambiguous radar in low signal-to-noise ratio environment, a novel weak target detection and tracking algorithm based on the compressed sensing (CS) and multiple model particle filter (MMPF) is proposed. The general solution is that constructing an over-complete atom dictionary according to the echo model of target, obtaining a sparse representation of the target echo signal with the CS method, and conducting a threshold detection with the obtained atom energy distribution and judge whether a target is present or not firstly; roughly extracting the ambiguous measurement of weak target by resolving the least square problem constrained by one-norm minimisation if a target is present then proposing an ambiguous measurement-based MMPF manoeuvring target tracking method, and realising an effective detection and tracking of manoeuvring weak target in the presence of range measurement ambiguity lastly. Simulation results demonstrate that the proposed method can improve the radar performance of target detection and tracking effectively, and succeeds in range ambiguity resolving.