Cooperative and Distributed Localization for Wireless Sensor Networks in Multipath Environments
Mei Leng, Wee Peng Tay, and Tony Q.S. Quek

TL;DR
This paper introduces a scalable, low-overhead distributed belief propagation algorithm for sensor localization in multipath wireless environments, enabling sensors to cooperatively self-localize with high accuracy.
Contribution
It presents a novel distributed localization method using belief propagation that works effectively in loopy networks with multipath effects.
Findings
Algorithm converges despite network loops
Achieves high localization accuracy
Low communication overhead
Abstract
We consider the problem of sensor localization in a wireless network in a multipath environment, where time and angle of arrival information are available at each sensor. We propose a distributed algorithm based on belief propagation, which allows sensors to cooperatively self-localize with respect to one single anchor in a multihop network. The algorithm has low overhead and is scalable. Simulations show that although the network is loopy, the proposed algorithm converges, and achieves good localization accuracy.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsIndoor and Outdoor Localization Technologies · Distributed Sensor Networks and Detection Algorithms · Target Tracking and Data Fusion in Sensor Networks
