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Research on Target Location and Tracking Algorithm in Wireless Sensor Networks

Author: DuFei
Tutor: LvJianPing
School: Suzhou University
Course: Signal and Information Processing
Keywords: Wireless sensor networks date-aggregation target tracking dynamic cluster remainder energy
CLC: TN929.5
Type: Master's thesis
Year: 2011
Downloads: 55
Quote: 1
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Abstract


Wireless sensor networks (WSNs) can monitor, sense, collect and manipulate information from kinds of monitored object. It is widely used in fields as military, environmental monitoring and industrial production and so on. Now WSNs is currently one of the hot new cutting-edge research in the international. For it has the advantage of self-organization, wide coverage, high fault-tolerance, high accuracy measurements, as well as the features of low cost, low power, flexible deployment etc, WSNs is applied to military and abundant civil fields.This paper made a deep study of the tracking position in the environment of WSNs and data-aggregation algorithm. Based on the requirement of maximization of the life circle of WSNs, the paper proposed a dynamic process of target tracking DTA(Dynamic Tracking Algorithm) based on message driven, improving the tracking precision and the life circle of the network. In other words, track and monitor the target by waking up the nodal points clusters around the target within a certain area. As the target moves, the structure of the cluster changes continuously, avoiding the waste of the energy by blindly waking up some unnecessary nodal points.The optimum proposal of DTA mainly concerned the network load balancing. The proposal made a analysis of the density of the layout of the nodal points, and consider comprehensively the dump energy in the process of the data transmission and the signal strength the nodal points receive from the target. Try to avoid the nodal points with little dump energy to the greatest extent, in order to realize the aim of balancing the energy consumption and improving the life circle of the network and realize the load leveling of the nodal points. The experimental results showed that the network energy consumption of the algorithm of DTA and during the working periods of the neural network, the number of the survival nodal points of the whole network improves. Especially in the large and medium-sized senor network, the algorithm has obvious advantages in the energy conservation and load balancing. The MRDA (Minimum Routing based Date-aggregation Algorithm) proposed in this paper also obvious better than the GIT in the data transfer process.

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