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ZHANG Shunsheng, CAI Zihan, and LIU Yongxu. Synthetic aperture passive localization of a single-satellite multi-radar emitter via time-frequency parameter estimation[J]. Journal of Radars, in press. doi: 10.12000/JR25165
Citation: ZHANG Shunsheng, CAI Zihan, and LIU Yongxu. Synthetic aperture passive localization of a single-satellite multi-radar emitter via time-frequency parameter estimation[J]. Journal of Radars, in press. doi: 10.12000/JR25165

Synthetic Aperture Passive Localization of a Single-satellite Multi-radar Emitter via Time-frequency Parameter Estimation

DOI: 10.12000/JR25165 CSTR: 32380.14.JR25165
Funds:  The National Ministries Projects
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  • Corresponding author: ZHANG Shunsheng, zhangss@uestc.edu.cn
  • Received Date: 2025-09-03
  • Rev Recd Date: 2025-11-07
  • Available Online: 2025-11-11
  • Passive localization methods based on synthetic aperture imaging offer high positioning accuracy. However, in scenarios involving multiple radar emitters transmitting Linear Frequency-Modulated (LFM) signals, distinguishing signals that are overlapped in the time and frequency domains can be challenging. This phenomenon, known as phase overlap, results in a significant degradation of localization performance. To address this issue, the present paper proposes a single-satellite multi-radar-emitter passive localization method based on synthetic aperture imaging using time-frequency parameter estimation. First, a signal model for multiple radar emitters transmitting LFM signals is constructed. The time-frequency parameters of the multiple radar emitter signals are estimated concurrently via a combination of Short-Time Fourier Transform (STFT) and DBSCAN. A rapid approximation of the azimuth chirp rate is attained through a coarse-to-fine search strategy founded upon the use of the STFT. The accurate localization of multiple radar emitters is ultimately realized through the implementation of two-dimensional focusing in the range and azimuth dimensions. The Cramer-Rao lower bound of the proposed method is derived on this basis. The experimental findings demonstrate that the proposed method enhances the localization accuracy by approximately 10 km at a signal-to-noise ratio of −10 dB, in comparison with the enhanced real-valued space-time subspace data fusion-based direct positioning method. Moreover, it reduces the computational time by half relative to the CLEAN-based synthetic aperture multi-source localization approach.

     

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