首页|LFM Radar Source Passive Localization Algorithm Based on Range Migration

LFM Radar Source Passive Localization Algorithm Based on Range Migration

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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 aper-ture (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 uncoopera-tive system transceivers. Furthermore, it requires data containing a satellite flying over the radia-tion 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 dif-ficulty 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 interpola-tion, 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 scenar-ios. Finally, the effectiveness of this algorithm is verified through simulations.

passive localizationrange migrationresidual frequency offset

Dandan Li、Deyi Wang、Hao Huan

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Beijing Key Laboratory of Fractional Signals and Systems, School of Information and Electronics, Beijing Institute of Technology, Beijing 100081, China

Beijing Aerospace Automatic Control Institute, Beijing 100854, China

国家自然科学基金

62027801

2024

北京理工大学学报(英文版)
北京理工大学

北京理工大学学报(英文版)

影响因子:0.168
ISSN:1004-0579
年,卷(期):2024.33(2)
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