Research On Coverage Optimization And Target Localization Technology For Wireless Sensor Networks

Wireless Sensor Network (WSN) is made up of sensor nodes with the abilities of sensing, computing and communicating; WSN can be widely applied in many fields such as industry, agriculture, national military defense, environmental monitoring, space exploration, medical treatment and etc. Coverage optimization and target localization are the premises of realizing many applications of WSN. Network coverage is considered to be a primary problem in network designing which determines the service scope of wireless sensor network, influences the cost of network and concrete performances largely, and the target localization provides location service for the entire network, which is the prerequisite of realizing vast application of WSN. Researches on coverage optimization and target localization based on WSN are presented in this dissertation, the main contents and results in the paper are the following:The coverage optimization algorithm of hybrid network based on mobile nodes is presented in the dissertation for the lack of coverage areas which are caused by nonuniform distribution or the failure of sensor nodes. The node sensing model supporting the false-alarm rate is adopted to calculate the network collaborative detection probability, and the virtual mobile strategy of nodes is proposed in allusion to the limited energy of mobile nodes. Simulation results show that the proposed method could accomplish the network coverage optimization and realize a more reasonable node deployment and increase the network lifetime with limited mobile nodes.The network redeployment algorithm based on energy balance is put forward which is aiming to the coverage holes in static wireless sensor networks deployed randomly. The network status model is established based on the cooperative detective probability and energy distribution with the sensor nodes, and the edges of coverage holes are extracted accurately though the image binarization and morphological approach, then the best positions of redeployment nodes are found out by Delaunay trianglation algorithm in this method. Simulation results show that the proposed algorithm could repair the network coverage holes with little added nodes, increase the network coverage rate and improve the network service quantity effectively.The sound source localization based on particle swarm optimization algorithm is proposed in wireless sensor networks. The model of sound source localization is established which applies the location algorithm based on time difference of arrival method and maximum likelihood estimation method utilizing the different propagation speed between radio-frequency signal and sound signal, and the problem of sound source localization is converted to the extreme value problem of nonlinear function which is solved by particle swarm optimization algorithm finally. The simulation results show that the proposed algorithm is better than classical localization algorithms and has higher estimation accuracy.The target localization algorithm based on beacon node selection scheme is proposed aiming to the issue on the Non-line of Sight (NLOS) errors and the estimation errors of beacon nodes, which could inhibits the disadvantageous influence to target localization from the obstacles in noise environment. The simulation experiment indicates that the proposed algorithm comparing with algorithms using all the nodes and random selection of nodes could restrain the disturbance errors effectively and lead to higher location accuracy under the conditions with different parameters.Multi-target fault-tolerrant localization algorithm in binary wireless sensor network is investigated. The classification method of alarm nodes based on K-Means clustering is put forward for the problem of multiple targets which is not affected by the position of targets and suitable for multiple target sources. The K-Means Clustering-Improved subtract on negative add on positive add on positive (KMC-ISNAP) fault-tolerrant algorithm is applied to solve the false alarm of beacon nodes, and influencing factors is used to reduce the effect of fuzzy nodes. The simulation results illustrate that the proposed KMC-ISNAP has higher estimation accuracy and better fault tolerance than other algorithms with different number of beacon nodes, false alarm node ratio and cell length.An indoor localizing system with high precision based on time difference of arrival between radio frequency and ultrasonic signal is designed, which could localize the mobile target node fast and accurately. Target node sends radio frequency and ultrasonic signal to beacon nodes simultaneously, and beacon nodes send the received signal to the sink node through the wireless way, then sink node calculate the distance between target node and beacon nodes and transmit to PC machine by the serial port communication. PC machine use estimation algorithm based on PSO to realize the target localization according to the coordinate system, the coordinate of beacon nodes and distance information. The experimental results show that the positioning system has high accuracy and the biggest positioning error is within 4.3 cm.