ArticleSensors (Basel, Switzerland)2020
An Efficient NLOS Errors Mitigation Algorithm for TOA-Based Localization.
Article in Sensors (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
2 citing papers in PubMed.
- Research on Autonomous and Collaborative Deployment of Massive Mobile Base Stations in High-Rise Building Fire Field.Sensors (Basel, Switzerland) · 2023Article
- Spatial Multi-Source Information Fusion Localization Algorithm in Non-Line-of-Sight Environments.Sensors (Basel, Switzerland) · 2023Article
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Authors and funding
2 authors.
Funding
Abstract
In time-of-arrival (TOA) localization systems, errors caused by non-line-of-sight (NLOS) signal propagation could significantly degrade the location accuracy. Existing works on NLOS error mitigation commonly assume that NLOS error statistics or the TOA measurement noise variances are known. Such information is generally unavailable in practice. The goal of this paper is to develop an NLOS error mitigation scheme without requiring such information. The core of the proposed algorithm is a constrained least-squares optimization, which is converted into a semidefinite programming (SDP) problem that can be easily solved by using the CVX toolbox. This scheme is then extended for cooperative source localization. Additionally, its performance is better than existing schemes for most of the scenarios, which will be validated via extensive simulation.
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Registered trials
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