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Wireless sensor network multi-target tracking method for fuzzy clustering particle filtering

A multi-target tracking and wireless sensor technology, applied in the field of wireless sensor networks, can solve problems such as false association, multi-target tracking confusion, target loss, etc., to achieve accurate tracking, avoid multi-target track loss and false association, and reduce complexity. Effects of Sexuality and Computational Volume

Inactive Publication Date: 2010-02-03
MAOMING COLLEGE
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Problems solved by technology

[0008] In a dense multi-echo environment, for close-range and track-crossing targets, the echo closest to the predicted state of the target is not necessarily the target echo, and there may be a situation where a measurement belongs to multiple targets, so the In this case, the algorithm is prone to misassociation, resulting in multi-target tracking confusion and target loss.

Method used

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  • Wireless sensor network multi-target tracking method for fuzzy clustering particle filtering
  • Wireless sensor network multi-target tracking method for fuzzy clustering particle filtering
  • Wireless sensor network multi-target tracking method for fuzzy clustering particle filtering

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[0037] The wireless sensor network multi-target tracking method provided by the fuzzy clustering particle filter provided by the present invention first performs rough association on the measurement data of the sensor nodes based on the tracking threshold algorithm, eliminates part of the clutter, and then passes through the observation space of each sensor node Respectively establish their own FCM algorithms for fine correlation, perform linear optimal fusion of the fine correlation data, and finally use PF filter to predict the state of each target.

[0038] The main steps:

[0039] Threshold coarse association:

[0040] In a cluttered environment, each sensor measurement may be from the target or from the clutter. Considering the actual background and extreme motion state of the target, the measurement that is greatly different from the predicted state of the target cannot come from the target, so a rough correlation threshold can be set to exclude some impossible measurem...

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Abstract

The invention discloses a wireless sensor network multi-target tracking method for fuzzy clustering particle filtering. Firstly, the method performs coarse relevance based on tracking threshold algorithm to sensor node measuring data for eliminating parts of clutter; fine relevance data is subject to linear optimum blend by establishing respective FCM algorithm for fine relevance in the observation space of each sensor node; and finally particle filtering is used for predicting the state of each target. The invention can effectively avoid multiple-target track loss and error relevance and realize precise tracking of multiple targets.

Description

technical field [0001] The invention relates to the field of wireless sensor networks, in particular to a multi-target tracking method for wireless sensor networks based on fuzzy clustering particle filter. Background technique [0002] Multi-target tracking based on wireless sensor network (WSN) is an important research direction of multi-target tracking. Due to the outstanding advantages of low node cost, small size, wireless communication, network random deployment, good self-organization, robustness and concealment, WSN has broad application prospects in the field of multi-target tracking. However, WSN itself has the characteristics of limited resources such as node computing, energy, storage, and communication, which makes the more mature research results of traditional multi-target tracking unable to be directly applied to WSN systems. The multi-target tracking technology based on WSN is 21 A challenging research topic of the century. [0003] In WSN multi-target tra...

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Application Information

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IPC IPC(8): G01S13/66
Inventor 刘美陈政石徐小玲
Owner MAOMING COLLEGE
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