Wireless Location Tracking via Complex-Domain Super MDS with Time Series Self-Localization Information
Yuya Nishi, Takumi Takahashi, Hiroki Iimori, Giuseppe Abreu, Shinsuke Ibi, Seiichi Sampei
Abstract
We propose a wireless localization algorithm based on complex-domain super multidimensional scaling (CD-SMDS) augmented with a self-localization (SL) component, whereby each target tracks its own motion by incorporating bearing information, obtained e.g., from integrated inertial sensors. The proposed method improves localization accuracy by simultaneously using the time series information of distance and angle associated to the SL information in order to construct the SMDS rank-one edge kernel matrix, maximizing the noise reduction effect of the low-rank truncation via singular value decomposition (SVD). The efficacy of the proposed method over the original CD-SMDS is confirmed via software simulations, and compared with an SL-aware Cramér-Rao lower bound (CRLB).
BibTeX
@inproceedings{icassp2023_wirelesslocation,
title = {Wireless Location Tracking via Complex-Domain Super MDS with Time Series Self-Localization Information},
author = {Yuya Nishi and Takumi Takahashi and Hiroki Iimori and Giuseppe Abreu and Shinsuke Ibi and Seiichi Sampei},
booktitle = {ICASSP 2023},
year = {2023}
}