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In wireless sensor networks (WSNs), ultra-wideband (UWB) technology is essential for robot localization systems, especially for methods of the simultaneous estimation of position and orientation. However, current approaches frequently depend on rigid body models, which require multiple base stations and lead to substantial equipment costs. This paper presents a cost-effective UWB SL model utilizing the angle of arrival (AOA) and double-sided two-way ranging (DS-TWR). To improve localization accuracy, we propose a self-localization algorithm based on constrained weighted least squares (SL-CWLS), integrating a weighted matrix derived from a measured noise model. Additionally, we derive the constrained Cramér–Rao lower bound (CCRLB) to analyze the performance of the proposed algorithm. Simulation results indicate that the proposed method achieves high estimation accuracy, while real-world experiments validate the simulation results.
Details
; Xu, Hongbiao 2 ; Li, Zhan 3 ; Li, Ye 3 ; Yin, Guangqiang 4 ; Wang, Xinzhong 5 1 Institute of Information Technology, Shenzhen Institute of Information Technology, Shenzhen 518000, China;
2 Shenzhen Institute for Advanced Study, University of Electronic Science and Technology of China, Shenzhen 518000, China;
3 School of Information and Software Engineering, University of Electronic Science and Technology of China, Chengdu 610054, China;
4 School of Information and Software Engineering, University of Electronic Science and Technology of China, Chengdu 610054, China;
5 Institute of Information Technology, Shenzhen Institute of Information Technology, Shenzhen 518000, China;