A Small-Dimension-Dictionary Sparse Model for OFDM-Based Passive Radar

In passive radar using sparse representation theory to generate a range-Doppler (RD) map that can achieve better resolution than traditional methods, but has an obvious disadvantage, which is the high computational complexity due to the large dimension of the sparse dictionary. Therefore, basing on a special signal processing method in orthogonal frequency division multiplexing signals, the Doppler channel detector(CHAD), a new passive radar sparse model with a small-dimension-dictionary is proposed. And then the passive radar target detection method is established, considering the sparsity of the CHAD function of the echo signal in the range-Doppler domain. Simulation and experimental results show that the sparse model we proposed has high detection performance while avoiding the problem of too large dimensions of the sparse dictionary.