Accelerating Target Detection in Passive Radar Sensors: Delay-Doppler-Acceleration Estimation

Passive bistatic radars (PBRs) need to use long integration times to achieve ranges of interest for air traffic surveillance applications. However, with the increase of integration time, classical target detection algorithms used in passive radars encounter some limitations in detecting accelerating targets. This is mainly due to a simplified target’s motion model used for detector design. In such cases, the mismatch between the target’s simplified motion model and that of the actual target motion limits any improvement in signal-to-noise ratio. To cure this especially in the presence of the accelerating targets, we obtain the received signal model and formulate target detection problem as an M-ary hypothesis testing problem. Then, we apply generalized likelihood ratio principle to derive a new 3-D sequential detection algorithm. In the proposed detector, range-Doppler-acceleration coordinates of detectable targets are estimated as compared to the classical target detection algorithms with range-Doppler estimations. To effectively implement the proposed detector over the desired range-Doppler-acceleration map, we use a modified version of chirp fast Fourier transform. We also obtain a closed-form expression for false alarm probability to adjust the detection threshold. Simulation results are provided to illustrate the superiority of the proposed 3-D-detection algorithm over state-of-the-art classical target detection algorithm given in the context of FM-based PBR systems.