Passive Localization Algorithm for PRI-staggered Radar Signal Based on RMD and NUFFT

Passive synthetic aperture (PSA) is recently utilized in passive localization, due to its high-precision and high-resolution. However, the unknown parameters of the radiation sources will cause to Doppler signal to distort, which will affect the localization accuracy. To solve the problem, this paper proposes a passive localization algorithm based on range migration difference (RMD) and nonuniform fast Fourier transform (NUFFT) for PRI-staggered radar signal. The main idea is to use the RMD to compensate for the PRI estimation errors, then the azimuth distance can be derived by conducting quadratic polynomial fitting on the trajectory of the range migration. Moreover, the nonuniformly sampling of the Doppler signal caused by staggered PRI is corrected by achieving NUFFT via the convolution function. Therefore, the Doppler rate and zero-Doppler time can be estimated by designing different matched filters in frequency domain, and the carrier frequency estimation error is eliminated by searching the output peak value of the matched filters under different residential frequency offsets. The simulation results show that the proposed RMD-NUFFT method can not only eliminate the impact of radar parameter estimation error on localization accuracy, but also achieve accurate parameter estimation for nonuniformly sampled signals, improving the positioning accuracy of the target. Furthermore, compared with traditional DOA, FOA and TDOA, the localization accuracy of proposed algorithm has a significant improvement. The estimation error of source position does not exceed 800 m with SNR not less than –5 dB, which proves the effectiveness of the proposed method.