An identification method of LBL underwater positioning systematic error with optimal selection criterion

Unlike the space targets such as satellites whose observation distance is about the order of 100 km, the measurement distance of long baseline (LBL) underwater positioning system is much shorter. If the noncoincidence between the multiple beacons and the target center is not considered, this systematic error will cause a little larger positioning error. Therefore, aiming at the situation that multiple beacons are installed outside the target and the distance between the beacons and the target center is significant, a multi-beacon positioning model of the LBL underwater system is constructed in this paper. Furthermore, for the sound speed systematic error and the time of arrival (TOA) systematic error in the multi-beacon LBL system positioning measurement data, three identification models of systematic error are constructed. According to the positioning process of the LBL underwater system, the expression of the optimal test statistic D is derived based on the TOA residual. Finally, the optimal selection criterion is given, and the underwater target position and systematic error can be accurately estimated. Both of the numerical simulation and the underwater positioning test show that the appropriate identification model of systematic error in the measurement data can be selected according to the optimal selection criterion, and the underwater target positioning accuracy of the LBL system can be improved.

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Publication Details

Journal
Scientific Reports
Published
2024-09-13
DOI
https://doi.org/10.1038/s41598-024-72247-9
Citations
5
Primary Topic
Target Tracking and Data Fusion in Sensor Networks
Type
article
Field-Weighted Citation Impact
1.74

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article

An identification method of LBL underwater positioning systematic error with optimal selection criterion

Xuanying Zhou, Zhangming He, Jiongqi Wang, Yao Xing et al.
5 citations
Scientific Reports
Target Tracking and Data Fusion in Sensor Networks
1.74
article

An identification method of LBL underwater positioning systematic error with optimal selection criterion

Xuanying Zhou, Zhangming He, Jiongqi Wang, Yao Xing, Yuyun Chen
article en
5 citations

Abstract

Unlike the space targets such as satellites whose observation distance is about the order of 100 km, the measurement distance of long baseline (LBL) underwater positioning system is much shorter. If the noncoincidence between the multiple beacons and the target center is not considered, this systematic error will cause a little larger positioning error. Therefore, aiming at the situation that multiple beacons are installed outside the target and the distance between the beacons and the target center is significant, a multi-beacon positioning model of the LBL underwater system is constructed in this paper. Furthermore, for the sound speed systematic error and the time of arrival (TOA) systematic error in the multi-beacon LBL system positioning measurement data, three identification models of systematic error are constructed. According to the positioning process of the LBL underwater system, the expression of the optimal test statistic D is derived based on the TOA residual. Finally, the optimal selection criterion is given, and the underwater target position and systematic error can be accurately estimated. Both of the numerical simulation and the underwater positioning test show that the appropriate identification model of systematic error in the measurement data can be selected according to the optimal selection criterion, and the underwater target positioning accuracy of the LBL system can be improved.

Scientific ReportsVol. 14(1)
National University of Defense Technology (CN)
National Natural Science Foundation of China
Life below water
Openalex Percentile: Top 13%
Target Tracking and Data Fusion in Sensor Networks
1.74
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An identification method of LBL underwater positioning systematic error with optimal selection criterion — Xuanying Zhou, Zhangming He, et al. · Scientific Reports (2024) | TGRS Research Map | TGRS