SINSDVL alignment correction method and system, medium and equipment

Abstract

The invention belongs to the technical field of navigation systems, and discloses an SINSDVL alignment correction method and system, a medium and equipment, and the SINSDVL alignment correction method comprises the steps: constructing a reference speed and a DVL output speed into two point sets, and converting a calibration problem into a Wahba problem; introducing a particle swarm algorithm into an error estimation problem, and establishing an estimation model based on the particle swarm algorithm; and establishing a particle swarm algorithm fitness function according to the installation error and the scale factor error between the SINS and the DVL sensor, estimating a constant error matrix, and further estimating a scale factor and an installation misalignment angle between the SINS and the DVL sensor. Simulation experiment and semi-physical experiment results show that the correction method can quickly and accurately estimate the scale factor and the installation misalignment angle between the SINS and the DVL sensor, so that the integrated navigation precision is greatly improved, the carrier does not need to do special motion or uniform-speed motion, and the coorection method is simple and high in alignment speed.

Description

technical field [0001] The invention belongs to the technical field of navigation systems, and in particular relates to a SINSDVL alignment correction method, system, medium and equipment. Background technique [0002] At present, the navigation system is indispensable for autonomous underwater vehicles (AUVs) to perform tasks. The AUV navigation system provides real-time navigation information, including speed, position, attitude, etc. Accurate navigation information is one of the guarantees for the AUV to successfully complete its mission. In the underwater environment, the main navigation equipment of AUV is the strapdown inertial navigation system (SINS). Although SINS can provide high-precision navigation information in a short period of time, because it is an integral calculation system based on Newton's law of inertia, it needs to integrate the output of the inertial measurement unit (IMU), that is, the gyroscope and the acceleration sensor. Errors that grow rapidly...

AI Technical Summary

Problems solved by technology

[0006] (1) The accuracy of SINS / DVL integrated navigation depends on the accuracy of sensor alignment and calibration, but due to the influence of various errors such as scale factor error and installation error, the navigation result is not ideal

[0007] (2) The existing calibration alignment method only considers the influence of the heading misalignment angle, but there are still large errors when only the heading misalignment angle is considered, which cannot meet the requirements of navigation accuracy

[0008] (3) The existing calibration and alignment methods require long-term uninterrupted GPS signals to provide navigation information to converge the estimated value, which is limited in practical application

[0009] (4) Existing correction alignment methods do not require the use of external auxiliary sensors, but AUVs must perform complex manipulations to obtain varying accelerations

[0010] (5) Existing correction alignment methods require specific trajectories and maneuvers, and are only effective when the misalignment angle is small and the carrier moves at a constant speed, and the training set and test set are required to meet the consistency requirements, which has limitations

However, errors such as installation misalignment angle and scale factor between SINS and DVL have a great influence on the accuracy of integrated navigation. In underwater vehicles that require high-precision navigation information, the integrated navigation error caused by the error between SINS and DVL is unbearable

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