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

Area of Science:

• Underwater acoustics
• Navigation systems
• Geophysics

Background:

• Long baseline (LBL) underwater positioning systems have shorter measurement distances compared to space-based systems.
• Non-coincidence between beacons and target center in LBL systems can lead to positioning errors.
• Existing models may not adequately address systematic errors in multi-beacon LBL setups.

Purpose of the Study:

• To develop a multi-beacon positioning model for LBL underwater systems accounting for beacon-target center non-coincidence.
• To construct systematic error identification models for sound speed and time of arrival (TOA) in LBL systems.
• To enhance the accuracy of underwater target positioning.

Main Methods:

• A multi-beacon positioning model for LBL systems was constructed.
• Three systematic error identification models were developed for sound speed and TOA errors.
• An optimal test statistic (D) based on TOA residual was derived.
• An optimal selection criterion for identification models was established.

Main Results:

• The study derived an optimal test statistic for identifying systematic errors.
• Numerical simulations and underwater tests validated the effectiveness of the proposed models.
• Accurate estimation of underwater target position and systematic errors was achieved.

Conclusions:

• The developed optimal selection criterion enables the appropriate identification of systematic error models.
• The proposed methods significantly improve the positioning accuracy of LBL underwater systems.
• The multi-beacon model effectively addresses errors arising from beacon-target center non-coincidence.