Robust Tdoa Indoor Tracking Using Constrained Measurement Filtering and Grid-Based Filtering

• Published in: Proceedings of the ... IEEE International Conference on Acoustics, Speech and Signal Processing (1998) pp. 4895 - 4899
• Main Authors: Huang, Rui, Tao, Jun, Yang, Le, Xue, Yanbo, Wu, Qisong
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.05.2020
• Subjects: constrained Kalman filter; Estimation; Filtering; grid-based filter; indoor localization; Kalman filters; Nonlinear optics; outlier-robust Kalman filter; Position measurement; Signal processing algorithms; Target tracking; TDOA
• ISSN: 2379-190X
• DOI: 10.1109/ICASSP40776.2020.9053618

This paper considers exploiting the time difference of arrival (TDOA) measurements from a ultra wideband (UWB) indoor positioning system to locate a moving point target. In indoor environments, measured TDOAs are subject to large errors due to multipath and/or non-line-of-sight (NLOS) propagation. Besides, they are nonlinearly related to the target position. This paper presents an enhanced two-step approach to achieve robust TDOA indoor tracking. Similar to the existing method, the first-step of the new algorithm preprocesses the raw TDOAs to mitigate the effect of large TDOA errors while its second step applies a recursively bounded grid-based filter (RBGF) to achieve target position tracking. To improve performance, in this work, the possible target position area, which is explicitly obtained by the RGBF, is fed back to the first-step such that a constrained TDOA measurement preprocessing is now performed. Extensive simulation results show that the newly proposed scheme offers better TDOA estimation and indoor target positioning accuracy over the original method and other benchmark algorithms.