Unmanned underwater vehicle target tracking method based on HuberM-Cubature Kalman filter

An underwater vehicle and Kalman filtering technology, which is applied in the direction of instruments, non-electric variable control, height or depth control, etc., can solve problems such as poor applicability, poor prediction accuracy, and complex calculation systems, and achieve nonlinear Robust filtering, the effect of avoiding interference

Active Publication Date: 2019-09-06
WUHAN UNIV OF TECH
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AI Technical Summary

Problems solved by technology

[0004] Bian Xinqian et al. applied the EKF filtering algorithm to the dead reckoning algorithm of UUV in "EKF's Dead Reckoning Algorithm for Unmanned Submersible Vehicles", and achieved good results

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  • Unmanned underwater vehicle target tracking method based on HuberM-Cubature Kalman filter

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Embodiment Construction

[0048] In order to make the object, technical solution and advantages of the present invention more clear, the present invention will be further described in detail below in conjunction with the examples. It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention.

[0049] Such as figure 1 Shown, a kind of unmanned underwater vehicle target tracking method based on HuberM-Cubature Kalman filter, comprises the following steps:

[0050] (1) Establish the equation of motion to simulate the motion of the underwater robot. First, model the motion law of the target. Assuming that the target moves in a straight line at a uniform speed in three-dimensional space, the motion equation of the target at time k+1 in the discrete time system It can be expressed as:

[0051] In the formula, x(k), y(k), z(k) are the position of the target at time k, and ΔT is the time interval for acquiring the ta...

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Abstract

The invention discloses an unmanned underwater vehicle target tracking method based on HuberM-Cubature Kalman filter. The unmanned underwater vehicle target tracking method based on the HuberM-Cubature Kalman filter comprises the following steps: 1) establishing a motion equation of an unmanned underwater vehicle; 2) establishing an observation equation of the unmanned underwater vehicle; and 3) using an UUV target tracking and localization algorithm based on the Huber-Cubature Kalman filter to establish the UUV motion model and observation model. The invention introduces a HuberM maximum likelihood estimation cost function into the Huber-Cubature Kalman filter and applies to the UUV target tracking and localization algorithm, and establishes the UUV motion model and observation model. Through reconstruction of CKF measurement information, and then filtering the nonlinear measurement information through a CKF algorithm, the interference of noise on the information is avoided, and nonlinear robust filtering is realized without the use of a traditional linearization method.

Description

technical field [0001] The invention relates to unmanned underwater vehicle technology, in particular to a method for tracking an unmanned underwater vehicle target based on HuberM-Cubature Kalman filtering. Background technique [0002] As one of the hot research directions in the marine field in recent years, the underwater unmanned vehicle has played an increasingly important role in the military field, fishery, underwater detection and many other aspects. As an important auxiliary tool for underwater detection, underwater maintenance, and underwater sample collection in specific areas, underwater unmanned vehicles provide scientific exploration for human beings, rational development of marine resources, improvement of my country's effective use of international sea resources, and smooth development of relevant scientific research. a reliable guarantee. [0003] At present, the target tracking of an unmanned underwater vehicle (UUV) mainly obtains the continuous azimuth a...

Claims

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Application Information

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IPC IPC(8): G05D1/06
CPCG05D1/0692
Inventor 范世东王斌
Owner WUHAN UNIV OF TECH
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