Emitter localization is an active research topic in electronic reconnaissance. Recently, passive synthetic aperture (PSA) is used to determine the azimuth and range distance of emitter. However, the existing methods approximate the distance equation of the spaceborne model through the airborne model, resulting in a large positioning error. In this paper, an emitter localization algorithm based on PSA in spaceborne model is proposed. First, the phase of the received signal is accumulated by using the symmetry of the Doppler history of the received signal in long synthetic aperture time, improving the azimuth positioning accuracy. The effective velocity is then used to establish the nonlinear equations of range distance. A modulus function is used to solve the equations, correcting the range positioning error in spaceborne model. Finally, the influence of noise, satellite position error, and satellite speed error on the positioning results is analyzed. The error matrix of proposed method in wide swath is obtained. Simulation results show that the positioning accuracy of this method is one order of magnitude higher than that of traditional single satellite positioning methods. The effectiveness of the proposed method is verified through actual satellite experiments.

Passive localization is important because of its strong concealment and long detection distance. Space-borne passive radiation source location technologies have contradicting characteristics of wide coverage and high-precision position. Hence, accurate target identification is difficult to realize. A novel measurement that utilizes passive synthetic aperture is presented in this letter to measure the time of the satellite’s passing zenith precisely. In the beam coverage duration, the radiation carrier Doppler component is extracted and accumulated to synthesize an equivalent large virtual satellite antenna azimuth aperture. Taking advantage of the linear Doppler rate, a local matched filter is designed to implement a 2-D search. Doppler rate and zero Doppler point correspond to the target range and azimuth locations, respectively. The corresponding subastral point position radiation source can then be determined. Practical experiment results from an unmanned aerial vehicle platform demonstrated the effectiveness, wide coverage, and high-precision meter scale of the proposed method. Satellite data were also utilized to verify the feasibility of the system.

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.