传感网中UWB和IMU融合定位的性能评估  

Performance Evaluation of UWB and IMU Fusion Positioning in Wireless Sensor Network

作　　者：段世红[1,2] 姚翠 徐诚[1,2] 何杰[1,2] Duan Shihong;Yao Cui;Xu Cheng;He Jie(School of Computer and Communication Engineering,University of Science and Technology Beijing,Beijing 100083;Beijing Key Laboratory of Knowledge Engineering for Materials Science(University of Science and Technology Beijing),Beijing 100083)

机构地区：[1]北京科技大学计算机与通信工程学院,北京100083 [2]材料领域知识工程北京市重点实验室(北京科技大学),北京100083

出　　处：《计算机研究与发展》2018年第11期2501-2510,共10页Journal of Computer Research and Development

基　　金：国家重点研发计划项目(2016YFC0901303);国家自然科学基金项目(61671056;61302065;61304257;61402033);北京市自然科学基金项目(4152036);天津市重大科技专项(16ZXCXSF00150)~~

摘　　要：位置信息是物体的基本属性之一.随着无线传感器网络(wireless sensor network,WSN)的蓬勃发展,传感器网络中节点位置信息的获取变得尤为重要.超宽带(ultra-wideband,UWB)和惯性测量单元(inertial measurement units,IMU)以其高定位精度,在WSN中得到了广泛应用.UWB精度高,但容易受多径效应和节点间的相对几何位置关系影响.IMU惯性测量单元能够提供连续的惯性信息,但累积误差问题难以解决.基于IMU和UWB结合的融合定位方法,能够在提高定位精度的同时补偿UWB的多径效应影响和IMU的误差累积问题.因此,提出一种新的基于UWB和IMU的融合定位方法,实现传感网中目标节点的高精度位置追踪,并通过计算克拉美罗下限(Cramer-Rao lower bound,CRLB)表征融合定位方法的空间定位性能验证其在解决多径和几何拓扑问题上的有效性,通过计算后验克拉美罗下限(posterior Cramer-Rao lower bound,PCRLB)表征融合定位方法的时间定位性能验证其在累积误差纠正上的有效性,为基于UWB和IMU融合定位算法的设计和仿真提供理论支持.实验结果表明:融合定位方法具有更好的时空定位性能,更能接近实际应用的理论精度下限.Location is one of the basic properties for an object.With the development of wireless sensor network(WSN),the requirements for sensor nodes location have become more and more important in practical applications.Ultra-wideband(UWB)and inertial measurement units(IMU)have been widely used in WSN due to their high positioning accuracy.UWB is of high accuracy but it is susceptible to multipath effects and relative geometric position relationships between nodes.IMU can provide continuous inertial information,but cannot solve the cumulative error problem.Thus,the fusion positioning method based on UWB and IMU can compensate the UWB multipath effect and IMU error accumulation problem,and finally improve the positioning accuracy.In this paper,a new fusion positioning method based on UWB and IMU is proposed to realize the high-precision position tracking of the target nodes in sensor network.The CRLB(Cramer-Rao lower bound)is calculated to characterize the spatial location performance of the fusion positioning method,and the PCRLB(posterior Cramer-Rao lower bound)is calculated to characterize the temporal positioning performance of the fusion localization method.Both CRLB and PCRLB are used to provide theoretical support for the design and simulation of the fusion positioning algorithms.Experimental results show that the proposed fusion method has better positioning performance in both temporal and spatial aspects,which is closer to the theoretical lower bound of practical application.

关 键 词：传感器网络 融合定位 超宽带 惯性测量单元 克拉美罗下限 后验克拉美罗下限 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]