Wireless sensor network object tracking method based on double layer forecast mechanism

A sensor network and wireless sensor technology, used in satellite radio beacon positioning systems, radio wave measurement systems, instruments, etc., can solve the problems of target motion model and system measurement model error, prior distribution affecting tracking accuracy, etc., to achieve prediction. The effect of smooth trajectory, less communication, and improved tracking accuracy

Inactive Publication Date: 2009-01-07
NAVAL UNIV OF ENG PLA
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Problems solved by technology

Bayes estimation is also a feasible method for WSN target tracking, but due to the error of the target motion model

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  • Wireless sensor network object tracking method based on double layer forecast mechanism
  • Wireless sensor network object tracking method based on double layer forecast mechanism
  • Wireless sensor network object tracking method based on double layer forecast mechanism

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Embodiment Construction

[0025] The present invention will be described in further detail below in conjunction with the accompanying drawings.

[0026] Nodes in the hierarchical WSN adopted by the present invention can be divided into common sensor nodes (Sensor Node, SN) and cluster head nodes (Cluster Head, CH) (for the structure of hierarchical WSN, refer to figure 1 ).

[0027] The specific implementation process of the present invention can be divided into 4 steps (see figure 2 ):

[0028] (1) The SN node calculates the target position. Remember the target position at time t is X t , X t =(x t ,y t ), the sensor measured value is z t ,Z t ={z 0 ,z 1 ,...,z t} represents the local historical measurement value of the sensor. The target state dynamic model is defined by the state transition probability p(X t+1 |X t ) is given; the sensor measurement model consists of the target state-measurement value transition probability p(z t |X t ) is given. The forecast and update calculation...

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Abstract

The invention relates to a target tracking method based on a double-layer forecasting mechanism in a sensor network, wherein, the sensor network is based on a hierarchical wireless sensor network and consists of an SN node and a CH node; the detailed steps of the invention are that the SN node adopts a Bayes estimation method to carry out the micro-forecast of a target location; the CN node obtains the observed value of the target location by combining the result of the SN node; based on a curvilinear motion equation, the CH node carries out the macro-forecast of the target location so as to obtain the estimated value of the target location; the CH node carries out the linear fitting of the observed value and the estimated value of the target location to solve a final target tracking location. The invention is technically characterized in that a WSN is fully utilized to realize the target tracking; the tracking method fully considers the needs of low complexity, low communication traffic and low energy consumption of the WSN target tracking method and passes a theoretical analysis and a simulated verification. The locating and tracking method in the invention is capable of accurately and quickly solving the motion parameters of the target by programmed location software.

Description

technical field [0001] The invention belongs to the technical field of wireless sensor network target tracking, in particular to a sensor network target tracking method based on a two-layer prediction mechanism. Background technique [0002] With the rapid development and maturity of MEMS, computer, communication, automatic control and artificial intelligence and other disciplines, a new type of measurement and control network - Wireless Sensor Network (WSN) has emerged. WSN integrates sensor technology, embedded computing technology, distributed information processing technology, and wireless communication and network technology. Nodes form a multi-hop self-organizing network system through Ad-hoc and other methods, which can sense, collect and process the network cooperatively. Monitor objects and various environmental information in the coverage area, and transmit it to users who need this information. [0003] Compared with independent satellite and ground radar trackin...

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Application Information

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IPC IPC(8): G01S5/02G01S5/12G01S19/24
Inventor 刘忠程远国李国徽彭鹏菲
Owner NAVAL UNIV OF ENG PLA
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