OPTIMIZING 5G BASE STATION SELECTION FOR PASSIVE RADAR ULTRA-LOW ALTITUDE TARGET LOCALIZATION

With the rapid advancement of 5G technology, passive radar systems have gained significant opportunities for progress in target localization. However, the high-density deployment of 5G base stations can substantially increase both construction and operational costs. To address this challenge, this paper proposes a novel approach for selecting 5G base stations with the aim of optimizing localization accuracy using fewer base stations. The method integrates considerations of 5G signal characteristics, the geographical distribution of base stations, and environmental factors to enhance the accuracy and reliability of passive radar localization. Based on the geometric dilution of precision (GDOP) theory, this paper develops a localization model for a multi-source, single-receiver system, incorporating site uncertainty and measurement errors to optimize base station configuration. Simulation results demonstrate that the proposed method outperforms traditional approaches in complex environments, offering a new perspective on the integration of communication and sensing in radar applications while optimizing resource allocation.