Robust High-Accuracy Cellular Base Station Positioning for User Equipment Based on Multi-Signal Fusion Passive Imaging

Emerging applications such as smart cities and smart transportation require sub-decimeter accuracy in user equipment (UE) location services to enhance safety and reliability. Therefore, robust high-accuracy positioning technology is crucial for these applications. However, existing two-step positioning methods rely on numerical solutions, which are susceptible to non-ideal factors, resulting in non-convergent solution errors of several meters, rendering accurate multi-target positioning difficult. We propose a cellular base station (BS) positioning method for UE based on a multi-signal fusion passive imaging algorithm. The proposed approach provides highly robust location services with sub-decimeter-level accuracy and enables simultaneous multi-target positioning. The algorithm decouples the phase difference from UE to distributed BSs into spatial frequency and reconstructs the spatial spectrum by fusing spatially sampled frequency points from the UE uplink multisignal. The UE is imaged as a point target to obtain its spatial distribution information. With the fusion of multi-signal received by distributed BSs, the integral side-lobe ratio and minimum discernible distance are improved, and the non-line-of-sight interference is suppressed, thus enhancing the robustness of positioning accuracy. Compared with the existing two-step methods through simulation, the proposed method demonstrates more robust positioning accuracy under the same non-ideal conditions. Field experiments demonstrate a maximum positioning error of approximately 5 cm, with decimeter-level accuracy even when the signal-to-noise ratio deteriorates to −15 dB. Additionally, multi-target positioning can be achieved directly without data association limitations.