A method for calibrating dvl error of model-free Doppler log

Abstract

The invention discloses a DVL error calibration method for a model-free Doppler log, which can realize high-precision error calibration without a priori DVL error model. The method includes the following steps: during the underwater movement of the underwater vehicle AUV, obtain the two-dimensional horizontal velocity information and vertical velocity information of the AUV respectively, and obtain the horizontal measurement of the Doppler log DVL set on the AUV Velocity and vertical velocity are measured. Construct a horizontal regression predictor, use the two-dimensional horizontal speed information as the output training sample, and the horizontal measurement speed of DVL as the input training sample, train the horizontal regression predictor, and obtain the trained horizontal regression predictor. In the same way, the trained vertical regression predictor is obtained. The trained horizontal regression predictor and the trained vertical regression predictor are combined to get the target predictor. The DVL speed measurement information is collected in real time as the input of the target predictor, and the output of the target predictor is the calibrated DVL measurement speed.

Description

technical field [0001] The invention relates to the technical field of navigation systems, in particular to a DVL error calibration method for a model-free Doppler log. Background technique [0002] High-precision underwater navigation and positioning are the basis of all ocean development activities and marine high-tech development, and play an extremely important role in many aspects. The navigation problem of underwater autonomous vehicle AUV becomes very challenging due to the complex working environment. Since the drift error of the inertial navigation system INS is inevitable and will accumulate over time, working for a long time will cause the navigation error to exceed the mission accuracy requirements. The high-precision Doppler log DVL can provide accurate speed information, and can correct the speed error accumulation of the INS in time, thereby improving the positioning accuracy. Therefore, INS / DVL integrated navigation is currently the most widely used underwa...

AI Technical Summary

Problems solved by technology

However, in practical applications, the DVL error model usually cannot be accurately modeled, because not all error terms can be considered, and these unaccounted DVL error terms will have a very large impact on the calibration accuracy

At the same time, there is no guarantee that the installation error angle between INS and DVL is small

It can be seen that, no matter from the calibration accuracy or the reliability of the algorithm, the traditional calibration algorithm has great limitations.

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