Journal of Northeastern University(Natural Science) ›› 2024, Vol. 45 ›› Issue (9): 1235-1243.DOI: 10.12068/j.issn.1005-3026.2024.09.003

• Information & Control • Previous Articles    

Improved WLS Ultra-wideband Positioning Algorithm Based on Error Factor

Lin LIU1, Yu-hao SONG2,1()   

  1. 1.Key Laboratory of Information Coding and Transmission,Southwest Jiaotong University,Chengdu 611756,China
    2.State Key Laboratory of Rail Transit Engineering Informatization (China Railway First Survey and Design Institute Group Co. ,Ltd. ),Xi’an 710043,China.
  • Received:2023-04-28 Online:2024-09-15 Published:2024-12-16
  • Contact: Yu-hao SONG
  • About author:SONG Yu-hao, E-mail: 544552319@qq.com

Abstract:

In order to improve the positioning accuracy of ultra?wideband (UWB) in non?line of sight (NLOS) scenarios, an improved weighted least square (WLS) algorithm based on error factor was proposed in this paper. A one dimensional convolutional neural network (1DCNN) is trained by using ranging values and real?time channel impulse response (CIR) features to achieve accurate prediction of error factor. Based on the predicted error factor, the weighting matrix of improved WLS algorithm is designed, and different base stations are given reasonable weights to improve the UWB positioning performance in NLOS scenarios. Static and dynamic measured data are collected from the real environment to verify the performance of the improved WLS algorithm. The experimental results show that the improved WLS algorithm has similar positioning performance to the least square (LS) algorithm and WLS algorithm in the line of sight (LOS) scenarios. In the NLOS scenarios, the improved WLS algorithm is obviously better than the LS algorithm and WLS algorithm, and can effectively restrain the NLOS error.

Key words: ultra?wideband, time of arrival, non?line of sight (NLOS), one dimensional convolution neural network (1DCNN), improved weighted least square (WLS) algorithm

CLC Number: