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Genetic particle filtering algorithm-based underwater target tracking and positioning method

A particle filter algorithm, tracking and positioning technology, applied in the field of target tracking, positioning and navigation, can solve the problems of little improvement in positioning accuracy and ineffective calculation

Active Publication Date: 2017-04-19
SOUTHEAST UNIV
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AI Technical Summary

Problems solved by technology

[0004] Since the mathematical model of underwater positioning is nonlinear, the general least squares, Kalman filter and other methods cannot be effectively solved
Applying the weighted least squares method or other classic iterative methods to solve the problem does not greatly improve the positioning accuracy

Method used

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  • Genetic particle filtering algorithm-based underwater target tracking and positioning method
  • Genetic particle filtering algorithm-based underwater target tracking and positioning method
  • Genetic particle filtering algorithm-based underwater target tracking and positioning method

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Embodiment Construction

[0044] The present invention will be further explained below in conjunction with the accompanying drawings and specific embodiments.

[0045] figure 1 The flowchart for tracking and locating underwater targets based on the genetic particle filter algorithm disclosed by the present invention includes the following steps:

[0046] (1) Deploy the underwater target tracking and positioning system: install m hydrophones in the water area, and install ultrasonic transducers and hydraulic depth gauges on the tracking and positioning targets;

[0047] In this embodiment, three hydrophones are used to distribute in the water area in the form of a triangular array.

[0048] (2) Establish a three-dimensional coordinate system in the water area and obtain the coordinates of the hydrophone (x j ,y j ,z j ), the measurement distance s between the tracking target and m hydrophones j , The depth h of the positioning target, where j∈(1,2,...,m) represents the serial number of the hydropho...

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Abstract

The invention discloses a genetic particle filtering algorithm-based underwater target tracking and positioning method. The method comprises the steps of (1) deploying an underwater target tracking and positioning system: installing m hydrophones in the water area, and installing an ultrasonic transducer and a water pressure depth gauge on a tracking and positioning target; (2) establishing a three-dimensional coordinate system in the water area, obtaining the coordinates (xj, yj, zj) of the hydrophones, the measurement distance sj between the tracking and positioning target and m hydrophones and the depth h of the positioning target, wherein j belongs to the range of 1, 2, .., and m and represents the serial numbers of hydrophones; (3) according to the measurement distance between the tracking and positioning target and the hydrophones, establishing a measurement equation; (4) tracking and positioning an underwater target based on the genetic particle filtering algorithm. In this way, the coordinate values of the tracking and positioning target at the moment k can be predicted. Compared with the prior art, the method is high in stability and positioning precision.

Description

technical field [0001] The invention belongs to the field of target tracking and positioning navigation, and in particular relates to an underwater target tracking and positioning method. Background technique [0002] The idea of ​​particle filter (PF: Particle Filter) is based on Monte Carlo methods, which uses particle sets to represent probability and can be used in any form of state space model. Its core idea is to express its distribution through random state particles drawn from the posterior probability, which is a sequential importance sampling method. Although the probability distribution in the algorithm is only an approximation of the real distribution, due to the non-parametric characteristics, it gets rid of the constraint that the random quantity must satisfy the Gaussian distribution when solving the nonlinear filtering problem, and can express a wider distribution than the Gaussian model. It also has a stronger modeling ability for the nonlinear characterist...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01S5/30
CPCG01S5/30
Inventor 陈熙源臧云歌刘晓方琳
Owner SOUTHEAST UNIV
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