JOURNAL ARTICLE

Kalman tracking for mobile location in NLOS situations

Abstract

This paper deals with the problem of nonline-of-sight (NLOS) in wireless communications systems devoted to location purposes. It is well known that NLOS biases time of arrival (TOA) and time difference of arrival (TDOA) estimates thus reducing accuracy of positioning algorithms. In order to achieve positioning error reduction the Kalman filter proposed for location estimation includes the time measurement bias for each base station (BS) as additional parameters to be estimated. The use of the Kalman filter allows then tracking, not only the position and speed of the mobile, but also the bias due to NLOS, yielding an accurate location prediction algorithm.

Keywords:
Non-line-of-sight propagation Multilateration Kalman filter Computer science Base station Time of arrival Mobile station Real-time computing Position (finance) Tracking (education) Wireless Global Positioning System Telecommunications Artificial intelligence Engineering

Metrics

74
Cited By
5.61
FWCI (Field Weighted Citation Impact)
8
Refs
0.96
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Indoor and Outdoor Localization Technologies
Physical Sciences →  Engineering →  Electrical and Electronic Engineering
Target Tracking and Data Fusion in Sensor Networks
Physical Sciences →  Computer Science →  Artificial Intelligence
Advanced Adaptive Filtering Techniques
Physical Sciences →  Engineering →  Computational Mechanics
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