AUV cooperative navigation method of maximum correntropy adaptive cubature particle filter

A technology of collaborative navigation and particle filtering, applied in navigation computing tools and other directions, which can solve problems such as difficulty in implementation and large amount of PF calculation.

Inactive Publication Date: 2018-12-25
HARBIN ENG UNIV
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Problems solved by technology

[0004] In addition, the traditional PF and the improved PF have a large amount of calculation when used, so they are no longer suitable for occasions with high real-time requirements
To this end, people proposed a PF algorith

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  • AUV cooperative navigation method of maximum correntropy adaptive cubature particle filter
  • AUV cooperative navigation method of maximum correntropy adaptive cubature particle filter
  • AUV cooperative navigation method of maximum correntropy adaptive cubature particle filter

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Embodiment 1

[0115] In the actual cooperative navigation, outliers often appear when measuring the speed and position, which will cause the accuracy of the traditional nonlinear filtering algorithm to decrease or even diverge. Therefore, it is necessary to use nonlinear robust filtering for outliers, usually applied The nonlinear robust filtering method based on MCCKF, HRUPF and IVBCKF is used to obtain the motion state of the target. However, in the case of outliers in the measurement noise, the above filtering method cannot meet the requirements. The MCACPF-based AUV cooperative navigation method provided by the present invention has higher robustness than the existing method, and can improve the precision of cooperative navigation under the condition that the measurement noise has outliers. The advantages of the present invention are illustrated below with specific implementation examples. combine image 3 It is a schematic diagram of the average positioning error curve of target posi...

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Abstract

The invention discloses an AUV cooperative navigation method of maximum correntropy adaptive cubature particle filter (MCACPF). The MCACPF is used for completing the state estimation problem in the AUV cooperative navigation process. During AUV cooperative navigation, a state equation and a measurement equation of the AUV cooperative navigation are reconstructed into a nonlinear recursive model, and then maximum correntropy cubature Kalman filter (MCCKF) is adopted in the framework of cubature particle filter (CPF) to generate an importance probability density function required in particle filter (PF), generated particles are then re-sampled by using a Kullback-Leibler distance (KLD) resampling method, and finally the estimation of an AUV state is obtained according to the algorithm flow of the CPF so as to realize the positioning of an AUV and complete the cooperative navigation. The MCACPF method is applied to the AUV cooperative navigation with outliers in measurement noise, higheraccuracy than existing PF, improved PF and robust filtering is obtained, and the computational complexity is lower than an existing improved particle filtering algorithm.

Description

technical field [0001] The invention belongs to the technical field of nonlinear robust filtering and cooperative navigation, and in particular relates to an AUV cooperative navigation method of Maximum Correntropy Adaptive Cubature Particle Filter (MCACPF). Background technique [0002] Using nonlinear filtering, such as Extended Kalman Filter (EKF), Unscented Kalman Filter (UKF), Particle Filter (PF), etc. Vehicles, AUV) cooperative navigation for positioning, due to the water lock phenomenon of the Doppler Velocity Log (DVL), multiple acoustic propagation paths between the sound source and the receiver lead to the reflection of sound waves, causing the sound velocity to vary with Depth changes, reflections on the water surface and the seabed and other reasons will lead to outliers in the measurement noise, which seriously affects the accuracy of multi-AUV cooperative navigation and positioning. To solve this problem, it is proposed to use the nonlinear Filtering (Huber N...

Claims

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Application Information

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IPC IPC(8): G01C21/20
CPCG01C21/20
Inventor 张勇刚范颖王国庆汪晓雨李宁
Owner HARBIN ENG UNIV
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