LFM Radar Source Passive Localization Algorithm Based on Range Migration

Traditional single-satellite passive localization algorithms are influenced by frequency and angle measurement accuracies, resulting in error estimation of emitter position on the order of kilometers. Subsequently, a single-satellite localization algorithm based on passive synthetic aperture (PSA) was introduced, enabling high-precision positioning. However, its estimation of azimuth and range distance is considerably affected by the residual frequency offset (RFO) of uncooperative system transceivers. Furthermore, it requires data containing a satellite flying over the radiation source for RFO search. After estimating the RFO, an accurate estimation of azimuth and range distance can be carried out, which is difficult to achieve in practical situations. An LFM radar source passive localization algorithm based on range migration is proposed to address the difficulty in estimating frequency offset. The algorithm first provides a rough estimate of the pulse repetition time (PRT). It processes intercepted signals through range compression, range interpolation, and polynomial fitting to obtain range migration observations. Subsequently, it uses the changing information of range migration and an accurate PRT to formulate a system of nonlinear equations, obtaining the emitter position and a more accurate PRT through a two-step localization algorithm. Frequency offset only induces a fixed offset in range migration, which does not affect the changing information. This algorithm can also achieve high-precision localization in squint scenarios. Finally, the effectiveness of this algorithm is verified through simulations. © 2024 Beijing Institute of Technology. All rights reserved.