Research On Distributed Multi-Sensor Target Tracking Algorithm

Wireless Sensor Networks(WSNs)are a distributed network composed of numerous wireless sensor nodes,which can sense the environment and collect data information.Among them,sensor nodes can be used to obtain a variety of information of interest,such as temperature,humidity,pressure,sound and light and other different types of elements,have a wide range of applications in many fields.Whether in military or civilian fields,WSNs has become an indispensable technical means,bringing more convenience and security to our life and work.In wireless sensor networks,sensor nodes usually use batteries as their power source.However,battery power inevitably faces a series of problems,Such as the inability to charge in time,limited energy and many other unfavorable factors.Therefore,when designing and improving algorithms,there is a trade-off between performance and power consumption.Firstly,a new energy constraint node planning algorithm is proposed for the distributed target tracking application in wireless sensor network.The goal of the algorithm is to maximize the target tracking performance,reduce the energy consumption of nodes as much as possible,and extend the network lifetime.This article first builds a node tracking model,and proposes a distributed connection network of cluster structures to reduce energy consumption by introducing node planning.In order to solve the complex constraints in the error matrix,this article proposes a method of energy constraint function and convex relaxation to simplify the optimization of such problems.The simulation results show that under the same energy consumption constraint,the algorithm proposed in this article can reasonably plan the nodes of participating in tracking to achieve better target tracking performance.Secondly,a node planning algorithm is proposed to solve the energy constraint in wireless sensor networks.Fully distributed target tracking algorithm improves tracking performance by consistency algorithm,but some sensor nodes contain less information and waste energy in the process of target tracking,which is not significantly helpful for improving tracking performance.And it will reduce the convergence speed of the consistent algorithm.Therefore,the node planning strategy is proposed in Chapter 3 to solve the problems in WSNs.This strategy is realized by planning and selecting some nodes and making them participate in the consistency algorithm.The convex relaxation method is used to solve complex integer programming problems.Combined with the node planning strategy,the energy consumption of the wireless sensor network can be reduced and the life of the wireless sensor network can be extended.Finally,in view of a variety of complex environments existing in wireless sensor networks,such as interference countermeasures,data loss,network congestion and other problems,direct transmission of observation data will produce large traffic and other problems.This paper presents a distributed algorithm based on its own data and neighboring decisions.Compared with the simple and direct process of exchanging observation data,this algorithm can reduce network traffic by passing decisions about the state of the environment.The simulation results show that the algorithm can converge quickly to the real state of the environment under the same communication overhead.Therefore,the algorithm has practical application value in complex environment such as confrontation.