Article Details

Abstract

To address the severe degradation of detection performance for low-altitude small targets caused by signal aliasing of multiple base stations in dense urban co-channel 5G networks, a robust separation technology based on sequential joint multi-reconstruction and extended cancellation is proposed. The method first detects the strongest Synchronization Signal Block (SSB), demodulates to obtain prior information comprising the Physical Cell ID and Master Information Block, and reconstructs a high-precision time-domain waveform of the SSB. Then, the Extended Cancellation Algorithm is applied to adaptively eliminate the signal and its multipath interference, and the aliased components are stripped one by one through iterative processing. Simulations under a typical urban low-altitude detection scenario verify that the proposed algorithm can completely separate all four co-channel signals and robustly achieve multi-base-station signal separation at Signal-to-Noise Ratios (SNRs) of 12 dB, 6 dB, and 4 dB. The proposed method effectively solves the problem of target echoes being masked by co-channel clutter and effectively improves the low-altitude detection capability of 5G passive radar.

Keywords

5G passive radar; co-channel base station interference; sequential reconstruction; Extensive Cancellation Algorithm (ECA)

References

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Funding

National Science and Technology Major Special Project (2024ZD1300100)

About the authors

Sun Qingyang (February 1990-), male, Han ethnicity, from Zaozhuang, Shandong, is a senior engineer and doctoral student. His research interests include integrated sensing, radar signal processing, and intelligence.