Low-Altitude Target Localization Method Based on Exogenous Radar with Multi-Base Station and 5G SSB Signals.

Yike Xu, Gangyi Tu, Luyan Zhang, Yi Zhou, Meiling Xiong, Yang Li

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Article in Sensors (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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Authors and funding

6 authors.

Yike XuSchool of Electronic and Information Engineering, Nanjing University of Information Science & Technology, Nanjing 210044, China.ORCID 0009-0005-9084-960X

Gangyi TuSchool of Electronic and Information Engineering, Nanjing University of Information Science & Technology, Nanjing 210044, China.ORCID 0000-0001-5722-8362

Luyan ZhangSchool of Electronic and Information Engineering, Nanjing University of Information Science & Technology, Nanjing 210044, China.

Yi ZhouSchool of Automation Engineering, Nanjing University of Information Science & Technology, Nanjing 210044, China.

Meiling XiongSchool of Electronic and Information Engineering, Nanjing University of Information Science & Technology, Nanjing 210044, China.

Yang LiSchool of Electronic and Information Engineering, Nanjing University of Information Science & Technology, Nanjing 210044, China.

Funding

NUIST Student's Platform for Innovation Training Program, National College Student Innovation and Entrepreneurship Training Program Supported Project XJDC202510300039

6 · The paper itself

Abstract

In this work, we propose a localization method based on an exogenous radar with multi-base station and the synchronization signal block (SSB) in 5G downlink signals. We combine physical cell identities (PCIs)-based identification with the extensive cancellation algorithm (ECA) to reconstruct and cancel the present strongest SSB signal, thereby obtaining reference signal receiving power (RSRP) values of them in descending order of strength. Then, we designed a two-stage localization method. Firstly, we determined the target's coarse location based on the directional characteristics of different SSB beams. Subsequently, we compared the RSRP values extracted from the actually received signals against those pre-obtained when the target is at various reference points. The reference point corresponding to the closest match was selected as the estimated target position. We conducted simulations under various signal-to-noise ratio (SNR) levels, reference point densities, and signal jitter conditions. The simulation results demonstrate that the method outperforms techniques such as Fang's method for time difference of arrival (Fang-TDOA) and observed time difference of arrival (OTDOA).

Indexed as

5G systemmulti-beamRSRPSSB detection and identification

Identifiers

PMID41977968

DOI10.3390/s26072183

PMCPMC13075243

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