JAIST Repository >
School of Information Science >
Articles >
Journal Articles >

Please use this identifier to cite or link to this item: http://hdl.handle.net/10119/16219

Title: Integrated Factor Graph Algorithm for DOA-based Geolocation and Tracking
Authors: Cheng, Meng
Aziz, Muhammad Reza Kahar
Matsumoto, Tad
Keywords: Factor graph (FG)
direction of arrival (DOA)
extended Kalman filter (EKF)
complexity analysis
Issue Date: 2020-03-09
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Magazine name: IEEE Access
DOI: 10.1109/ACCESS.2020.2979510
Abstract: This paper proposes a new position tracking algorithm by integrating extended Kalman filtering (EKF) and direction-of-arrival (DOA)-based geolocation into one factor graph (FG) framework. A distributed sensor network is assumed for detecting an anonymous target, where the process and observation equations in the state space model (SSM) are unknown. Importantly, the predicted state information can be utilized not only for filtering, but also for enhancing the observation process. To be specific, by taking the prediction into account as the a priori, a new FG scheme is proposed for GEolocation, denoted by FG-GE. The benefits are two-fold, compared with the conventional geolocation scheme which does not rely on the a priori information. First of all, significant performance improvement can be observed, in terms of the root mean square error (RMSE), when severe sensing errors are suddenly encountered. Furthermore, the proposed FG-GE can achieve dramatic reduction of computational complexity. In addition, this paper also proposes the use of a predicted Cramer-Rao lower bound (P-CRLB) to dynamically estimate the observation error variance, which demonstrates more robust tracking performance than that with only fixed average variance approximation.
Rights: Meng Cheng, Muhammad Reza Kahar Aziz, Tad Matsumoto, IEEE Access, 2020. DOI:10.1109/ACCESS.2020.2979510. This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/.
URI: http://hdl.handle.net/10119/16219
Material Type: publisher
Appears in Collections:b10-1. 雑誌掲載論文 (Journal Articles)

Files in This Item:

File Description SizeFormat
3067.pdf779KbAdobe PDFView/Open

All items in DSpace are protected by copyright, with all rights reserved.


Contact : Library Information Section, Japan Advanced Institute of Science and Technology