北京理工大学学报(英文版)2024,Vol.33Issue(2) :130-140.DOI:10.15918/j.jbit1004-0579.2023.135

LFM Radar Source Passive Localization Algorithm Based on Range Migration

Dandan Li Deyi Wang Hao Huan
北京理工大学学报(英文版)2024,Vol.33Issue(2) :130-140.DOI:10.15918/j.jbit1004-0579.2023.135

LFM Radar Source Passive Localization Algorithm Based on Range Migration

Dandan Li 1Deyi Wang 2Hao Huan1
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作者信息

  • 1. Beijing Key Laboratory of Fractional Signals and Systems, School of Information and Electronics, Beijing Institute of Technology, Beijing 100081, China
  • 2. Beijing Aerospace Automatic Control Institute, Beijing 100854, China
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Abstract

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.

Key words

passive localization/range migration/residual frequency offset

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基金项目

国家自然科学基金(62027801)

出版年

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
参考文献量2
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