【摘要】 在无线定位领域，超宽带（UWB）技术虽已获得广泛应用，但其定位精度易受复杂环境因素的显著干扰。为突破此瓶颈，该文提出一种基于信号分解的TFP-EKFT定位算法，用于标签位置信息的解算。通过构建模拟场景与实验环境分析验证，结果表明，该算法在标签存在旋转运动的密闭环境中仍表现出优异的鲁棒性；与现有主流定位解算算法的对比结果进一步证实，所提算法定位精度显著提升，且精度提升幅度超过50%。进一步结合IMU加速度信息进行协同分析，揭示出定位误差的主要来源为标签旋转运动，为未来三维复杂场景下的高精度定位技术发展提供了重要的理论依据与技术参考。更多还原

【Abstract】 In the realm of wireless localization,ultra-wideband(UWB) technology has achieved extensive adoption,however,its positioning accuracy is susceptible to significant degradation caused by complex environmental factors. To address this bottleneck,this paper presents a TFP-EKFT localization algorithm based on signal decomposition for resolving tag position information. Validation through the construction of simulated scenarios and experimental environments demonstrates that the proposed algorithm exhibits superior robustness even in confined spaces where tags undergo rotational motion. Furthermore,comparative analyses with existing state-of-the-art localization algorithms further confirm that the proposed algorithm achieves a remarkable improvement in positioning accuracy,with the enhancement exceeding 50%. Additionally,a joint analysis integrating inertial measurement unit(IMU) acceleration data reveals that the primary source of localization errors stems from tag rotation. These findings provide crucial theoretical insights and technical guidance for the advancement of high-precision localization technologies in future three-dimensional complex scenarios.更多还原