Optimal Estimation and Fundamental Limits for Target Localization Using IMU/TOA Fusion Method

Localization is one of the most important topics of the cyber-physical system. In the last decades, much attention has been paid to the precise localization and performance evaluation in wireless sensor networks. The inertial measurement unit (IMU) and time-of-arrival (TOA) fusion is a state-of-the-art method to solve the accumulative error and drifting problem faced by the sole IMU positioning and navigation method. Many of the existing studies are based on optimization. However, they usually face problems of non-convexity of the objective function, falling into local optimum, and the requirements for the prior/posterior probability distribution of measured values. All these reasons limit its practical applications toward accurate target tracking. This paper presents a Chebyshev-center-based optimization method. Geometrically considering the real position of the target, it aims at improving the target tracking accuracy. Cramér-Rao lower bound (CRLB) and posterior CRLB for IMU/TOA fusion are derived to characterize both the spatial and temporal localization performance of the proposed fusion method. The simulation results show that the proposed fusion method in this paper has obvious spatial-temporal performance advantages in theory. Practical use cases are also conducted, and the experimental results show that the proposed method significantly decreases the drift errors and has a lower tracking error compared with the state of the art.