A method for DVL calibration based on parameter estimation between two point sets

Abstract

ObjectiveIn order to improve the combined navigation accuracy of unmanned surface vehicles (USVs) by strapdown inertial navigation system (SINS) and doppler range finder (DVL), the DVL error needs to be accurately calibrated. MethodsThis paper carries out error modeling of the installation error angle, lever arm, and scale factor of the DVL, and focuses on the analysis of the impact of the lever arm error term on the combined navigation positioning in the vessels, pointing out the necessity of its calibration; proposes a DVL error calibration method based on the parameter estimation between two point sets, which treats the SINS/GNSS navigation parameters and DVL output parameters as two point sets, converting the calibration problem into an estimation problem of the difference between the two point sets, and using the Kalman filter to estimate the error parameters between the two point sets; using the SVD（singular value decomposition）-based observability analysis to quantify the observability of the filter in different motion condtions, giving the motion recommendations of the carrier during the calibration process.ResultsThe results of mathematical simulation and real ship experiments show that the global relative accuracy of the calibrated SINS/DVL algorithm can reach a voyage of 0.122%. During cornering maneuvers, the lever arm causes abrupt changes in SINS/DVL positioning. After compensating for the lever arm, the positioning errors become smoother and the overall positioning error is reduced.ConclusionThe proposed method provides a feasible way to calibrate each DVL error including the lever arm.

Keywords

• unmanned surface vehicles
• sins/dvl combined navigation
• dvl calibration
• lever arm error
• observability analysis