AUV (Autonomous Underwater Vehicle) cooperative navigation method based on maximum correntropy unscented particle filter

A technology of unscented particle filtering and collaborative navigation, applied in navigation computing tools and other directions to achieve the effects of excellent performance, improved accuracy and robustness

Inactive Publication Date: 2018-09-04
HARBIN ENG UNIV
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Problems solved by technology

[0004] The present invention provides an AUV collaborative navigation method based on the maximum cross-co

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  • AUV (Autonomous Underwater Vehicle) cooperative navigation method based on maximum correntropy unscented particle filter
  • AUV (Autonomous Underwater Vehicle) cooperative navigation method based on maximum correntropy unscented particle filter
  • AUV (Autonomous Underwater Vehicle) cooperative navigation method based on maximum correntropy unscented particle filter

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[0022] Below in conjunction with accompanying drawing, the present invention will be described in further detail:

[0023] The present invention is an AUV collaborative navigation method based on the maximum cross-correlation entropy unscented particle filter, comprising the following steps:

[0024] Step 1: Establish the state equation and measurement equation describing the AUV cooperative navigation system. The master-slave AUV co-location model is considered here, where the leader is the Communication and Navigation Aid (CNA). Since the depths of CAN and AUV can be accurately measured by pressure sensors, the 3D co-location problem can be simplified to a 2-D co-location problem. The state space model based on the acoustic ranging of the co-location system is as follows:

[0025]

[0026]

[0027] Among them, formula (1) is the state equation, formula (2) is the observation equation, x k and y k are the eastward and northward positions of the AUV at the kth moment...

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Abstract

The invention provides an AUV (Autonomous Underwater Vehicle) cooperative navigation method based on maximum correntropy unscented particle filter and belongs to the technical fields of nonlinear filtering and cooperative navigation. According to the method provided by the invention, a maximum correntropy unscented Kalman filter (MCUKF) algorithm is adopted, and state estimation in the AUV cooperative navigation process is solved. The method comprises the following steps: in the AUV cooperative navigation process, reconstructing a state equation and a measurement equation of cooperative navigation into a nonlinear recursive model, and processing by utilizing a maximum correntropy criterion; generating an importance probability density function needed in PF by adopting the MCUKF in a particle filter (PF) framework, and acquiring estimation of the AUV state according to an algorithm flow of the PF, so as to realize localization of the AUV and completing cooperative navigation. Accordingto the AUV cooperative navigation method disclosed by the invention, in AUV cooperative navigation in which measured noise has a burst value, more excellent performance than that of the conventional particle filtering, improved particle filtering and robust filtering can be achieved.

Description

technical field [0001] The invention relates to an AUV cooperative navigation method based on Maximum Correntropy Unscented Particle Filter (MCUPF), which belongs to the technical field of nonlinear filtering and cooperative navigation. Background technique [0002] Autonomous underwater vehicles (AUVs) are a modern technological product that integrates advanced technologies such as artificial intelligence, computer software, and sensors. It has a wide range of applications in marine resource exploration and development, underwater equipment inspection, and theater reconnaissance. Due to the deepening of human exploration and development of the ocean, the use of only a single AUV can no longer meet the requirements, so scientists have turned their attention to a collaborative system composed of multiple AUVs. Estimating the position information of AUV is a very important issue in AUV cooperative navigation. One of the commonly used methods is the filtering method based on t...

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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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