Multi-AUV synthetic location method based on combination of ant colony and extended Kalman filtering

Abstract

The invention aims to provide a multi- AUV synthetic location method based on combination of ant colony and extended Kalman filtering. The method comprises the steps of firstly establishing an AUV kinematic model, then conducting linearization on the AUV model, adopting a modified ant colony algorithm to conduct optimum estimations on a Q matrix and a R matrix; wherein the adoption of the modified ant colony algorithm specifically comprises the steps of at first adopting the ant colony algorithm to conduct transversal for the first time to obtain a large amount of solutions; adopting a particle swarm optimization to search a global optimum value; adopting again the ant colony algorithm to set the current solution as an initial start point of the ant colony, then choosing part of the most superior ants according to virtue or defect degrees of solutions obtained by the ants in the ant colony, and conducting weighted average to release pheromone according to virtue or defect degrees of quality of the solution; finally applying solved Q,R to an EKF, and thus location of AUV is achieved. According to the multi-AUV synthetic location method based on combination of ant colony and extended Kalman filtering, an intelligent algorithm and EFK are ingeniously combined, the problems that a noise matrix is uncertain, and hard to choose are solved, and filtering precision of EKF is improved; meanwhile, the application of combination of ant colony and extended Kalman filtering in a multi-AUV location system can sharply improve precision of the AUV location.

Description

technical field [0001] The invention relates to a co-location method for AUVs. Background technique [0002] With the continuous expansion of the research ocean area and the continuous complexity of military requirements, it will not be possible to achieve the expected goals only by relying on the independent work of a single underwater vehicle (AUV). A mainstream trend and direction of AUV development. The multi-AUV cooperative system has higher requirements for positioning accuracy. For example, each individual AUV must not only maintain its own high-precision positioning, but also always know the location information of the surrounding "partners" and its relative position in the collaborative system. If each individual in the AUV group is equipped with high-precision navigation equipment, this will greatly increase the cost. Therefore, a multi-AUV cooperative positioning technology has been proposed, that is, a small number of high-precision master AUVs are used to assi...

AI Technical Summary

Problems solved by technology

However, one of the most important problems in using EKF for positioning is the selection of the noise matrix. The accuracy and convergence of positioning depends largely on the user's prior knowledge of the noise matrix, that is, the system noise matrix and the measurement noise matrix. Pre-planned accuracy, if not chosen properly, the performance of EKF will be greatly reduced, or even not work properly

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