Dynamic clustering mechanism-based target tracking method for wireless sensor network

Abstract

The invention discloses a dynamic clustering mechanism-based target tracking method for a wireless sensor network. In the method, an initial cluster head is formed by a method for broadcasting the END values of nodes in a region; the residual energy of the nodes and distances from the nodes to a target are considered at the same time; in the process of selecting the nodes which participate in target tracking, the condition of the residual energy of the nodes is considered, and only the nodes that the received signal strength indicator (RSSI) signal strength of a received target is more than a certain threshold value are selected to participate in the tracking; the concept of a temporary cluster head is introduced into dynamic clustering adjustment, so that the target is not lost in the process of establishing a next cluster; and the target is tracked by a least square method so as to perform curve fitting on the track of the target. Based on a cluster head selecting mechanism with RSSI strength, factors such as a clustering algorithm, the residual energy of the nodes, the RSSI signal strength of the target and the like are considered, so that tracking precision is ensured, energy consumption is reduced, and the service life of the network is prolonged.

Description

Technical field [0001] The invention relates to a target tracking method used in a wireless sensor network, and belongs to the technical field of target tracking. Background technique [0002] Wireless sensor network is used to measure and control the environment, and one of the important applications is target tracking. Due to the small size and low price of sensor nodes, and the random deployment of sensor networks, which are self-organizing, robust and concealed, sensor networks are very suitable for the location and tracking of moving targets. On the other hand, wireless sensor networks have strict limitations on the battery energy and computing power of network nodes, a large number of nodes and high-density deployment, and complex network topology changes, which make relevant research extremely challenging. [0003] Many scholars at home and abroad have conducted in-depth research on single target tracking by wireless sensors, and have proposed many target tracking algorithm...

AI Technical Summary

Problems solved by technology

Zhang W S, Cao G H used the DCTC framework for wireless sensor network self-organization. This method ensures that the spanning tree has low energy consumption and high information acquisition at the same time by dynamically increasing and reducing nodes. The disadvantage is that the calculation is too complicated and difficult Application (based on energy efficient target tracking algorithm, Proc. of the IEEE Military Communications Conference, 2003: 597-602)

Wan Jiangwen proposed a dynamic cluster algorithm under time asynchronous conditions, which has good tracking accuracy and balances the energy consumption of the network. The defect is that the initial cluster head is selected as the node closest to the target, and energy factors are not considered (time asynchronous infinite sensor network Distributed Object Tracking. High Technology Communications, 2009: 1026-1030)

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