UWB Anchor Self-Localization Algorithm Based on PDOA and TOF

Ultra-wideband (UWB)-based indoor localization systems are characterized by high accuracy, strong anti-interference capabilities, low power consumption, and excellent scalability, making them a prominent technology in indoor positioning. Determining accurate anchor node positions is a prerequisite for achieving high-precision tag localization. However, this process often requires significant manual effort and time and may not be feasible for certain scenarios involving manual measurements. To address this challenge, this paper proposes an accurate and convenient anchor self-localization method. The proposed method requires only TOF and PDOA data from UWB measurements without relying on external sensor data, and can realize single-anchor localization without the need to introduce multiple anchors to construct a coordinate system. Subsequently, the iterative reweighted least squares (IRLS) algorithm is employed to centrally process measurement data from each anchor, yielding optimized position estimates. In simulation experiments, we analyzed the impact of ranging noise and AOA estimation errors on localization accuracy. Furthermore, we conducted validation experiments, and the results demonstrated that the proposed method effectively achieves accurate self-localization of UWB anchor nodes.