Target Parameter Estimation Method for Passive Radar Based on Compressed Sensing

Passive radar can estimate the range-Doppler information of the target by calculating the cross ambiguity function. But this method represents some problems, for example, the weak target can be masked by high sidelobes of strong target and low resolution. To solve these problems, a target parameter estimation method was proposed for passive radar based on compressed sensing. Firstly, a distributed compressed sensing simultaneous subspace pursuit algorithm was proposed to achieve the range domain sparse reconstruction. Then, taking an enlarged orthogonal matching pursuit algorithm, the Doppler domain sparse reconstruction was carried out. The results of simulation and measured data show that the proposed method can reduce the influence of the sidelobe generated by cross ambiguity function, improve the resolution, and avoid the problems of large dictionary size and high time complexity.