Sensor network distributed consistency object state estimation method

A sensor network and target state technology, applied in network topology, electrical components, wireless communication, etc., can solve problems that affect the quality of node target observation, cannot detect target blind nodes, and cannot maintain observation at any time

Active Publication Date: 2014-03-19
NAVAL AERONAUTICAL & ASTRONAUTICAL UNIV PLA
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Problems solved by technology

Therefore, the nodes in the network cannot keep observing all targets at any time, that is, there are blind nodes in the network that cannot detect targets at any time
Moreover, the change of the sensing model will affect the quality of the target observation of the node, and bring new challenges to key distributed tracking technologies such as network detection coverage, node cooperative control, and target state estimation.

Method used

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  • Sensor network distributed consistency object state estimation method
  • Sensor network distributed consistency object state estimation method
  • Sensor network distributed consistency object state estimation method

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Embodiment 1

[0069] Target tracking simulation scenarios such as figure 2 As shown, the monitoring area is a plane rectangle of 100m×100m, the sensor nodes are randomly distributed, and the target moves arbitrarily in the area. This embodiment intends to compare the performance of the distributed consistent state estimation method DMAP-KCF proposed by the present invention, the Kalman consistency filter method KCF, and the centralized optimal Kalman filter method CKF, and obtain the average value by 50 Monte Carlo simulations Experimental comparison results. The specific target state parameters, sensor parameters and consistency parameters are given below.

[0070] Target State Parameters

[0071] The target moves freely in the monitoring area, its initial position and speed direction are randomly determined, and the speed is randomly determined within the interval [1m / s 3m / s]. The goal state can be described as x=(x,y,v x , v y ) four-dimensional vector, where (x, y) is the target p...

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Abstract

The invention provides a sensor network distributed consistency object state estimation method. The method, based on information transmission between observation nodes of a sensor network, enables dynamic function division to be carried out on sensor nodes in the network, and observation node sets participating in consistency state estimation are adaptively optimized and selected in real time; on the basis of a distributed maximum a posteriori theory, weighting processing is performed on object prior information and measurement information; and with the influence of covariance of state estimation errors of different observation nodes on the calculation of average consistency state taking into consideration, and effective information consistency processing is performed, the distributed state estimation accuracy of each observation node can rapidly approach to the centralized estimation accuracy, state maintenance of blind nodes on an object is guaranteed, and the cases of endless emergence of new tracks and uncertainty of the tracks and the like can be effectively prevented.

Description

technical field [0001] The invention relates to an information fusion system of a sensor network, in particular to a method for estimating a distributed consistent target state of a sensor network, belonging to the field of sensor information processing. Background technique [0002] The distributed method is based on effective information exchange between nodes to realize resource sharing. It has the advantages of high fault tolerance, easy installation and expansion in large-scale networks, so it has attracted much attention in the research and application of distributed sensor networks. [0003] For the application of multi-target distributed tracking in sensor networks, among many distributed state estimation methods, the estimation algorithm based on consistency theory adopts an iterative method, and uses the effective information of neighbor nodes to continuously update the local estimation, so that each node can Independently calculate the global estimate after all th...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H04W24/00H04W84/18
Inventor 刘瑜何友王海鹏潘丽娜刘俊苗旭炳
Owner NAVAL AERONAUTICAL & ASTRONAUTICAL UNIV PLA
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