Application of Improved Robust Adaptive Algorithm in UWB/MEMS Positioning System

Abstract

An adaptive robust algorithm based on the tight combination of Ultra-Wideband (UWB) and Micro Electro Mechanical System (MEMS) is proposed to solve the problem that UWB is easily affected by non-line-of-sight (NLOS) errors in indoor environment, which result in low positioning accuracy. Firstly, the algorithm establishes a UWB/MEMS tight combination model. Secondly, the algorithm introduces the measurement error criterion based on the traditional robust algorithm. At the same time, aiming at the problem that the traditional robust algorithm has poor adjustment ability when part of the observations are interfered, and considering the actual situation that UWB is interfered by NLOS environment, a calculation method of multiple robust adaptive matrix is proposed. The filter gain matrix is regulated by the algorithm in real time according to different measurement errors, so that the filter has stronger adaptability. Comparing the improved algorithm with the traditional robust algorithm, the simulation results show that the improved adaptive filtering algorithm has better robustness and the positioning accuracy of UWB/MEMS integrated system has been significantly improved when the measurements are affected by abrupt noise and outliers.