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Method for synergetic fusion of distributed sensor network and positional correction of sensor

A distributed sensor and network collaboration technology, applied in navigation computing tools and other directions, can solve problems such as degradation, inaccurate sensor location information, and reduced fusion accuracy.

Active Publication Date: 2018-11-27
SHANGHAI JIAO TONG UNIV
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Problems solved by technology

[0004] Aiming at the problem that the consensus fusion of distributed sensors in the above-mentioned prior art may occur in practical applications due to the inaccurate position information of the sensor itself, the fusion accuracy may be reduced and deteriorated. The present invention proposes a variational Bayesian method based on Collaborative Fusion and Sensor Position Correction Method for Distributed Sensor Networks

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  • Method for synergetic fusion of distributed sensor network and positional correction of sensor

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Embodiment

[0063] This embodiment provides a distributed sensor network collaborative fusion and sensor position correction method, including the following steps:

[0064] Step 1: Each node of the sensor network is initialized to form initial parameters.

[0065] At each sensor node Given an initial target state estimate and estimated error variance in, is the set of all sensor nodes.

[0066] Step 2, each node of the sensor network performs prediction update.

[0067] In each step of fusion, each sensor node i uses the prediction step of Kalman filter to independently predict the target state, and calculate the predicted target state and update the estimated error variance matrix for the forecast At the same time, calculate the corresponding information matrix and information vector according to the target state and the estimated error variance matrix

[0068]

[0069] Step 3, each sensor node i in the sensor network obtains the measurement of the target state by the s...

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Abstract

The invention provides a method for the synergetic fusion of a distributed sensor network and the positional correction of a sensor. According to the method, a to-be-solved joint posterior distribution is approximated into the product of multiple distributions mutually independent through conditions, so that to-be-solved joint posterior distribution can be solved through an iteration VB algorithm.Meanwhile, the iteration process of a consistent algorithm is introduced into a variation iteration process, and the estimation of each node to a target state is restrained into an overall consistentresult through local communication between each sensor node and an adjacent neighbor node. A simulation result shows that the estimation precision of each sensor node to the overall target state andthe local position in the distributed sensor network can be effectively improved. The method can be applied to the fields of distributed sensor network radars, infrared target tracking, mobile robot positioning and the like.

Description

technical field [0001] The invention relates to a distributed sensor network collaborative fusion and sensor position correction method. Specifically, it involves a variational Bayesian (variational Bayesian, VB)-based consensus sensor fusion and self-position correction method. This method can be applied to the cooperative state estimation of distributed sensor networks, target tracking and other fields. Background technique [0002] In a sensor network composed of multiple sensors, the system's ability to perceive the external environment can be improved by fusing the observation information of multiple sensors. In a centralized sensor network, the measurement information obtained by each sensor node needs to be transmitted to a central node for centralized processing. In this way, it is theoretically possible to obtain an optimal estimate of the state from all sensor measurements. However, this centralized processing method brings a large communication burden to the se...

Claims

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Application Information

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IPC IPC(8): G01C21/20
CPCG01C21/20
Inventor 敬忠良沈楷董鹏
Owner SHANGHAI JIAO TONG UNIV
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