Research on target tracking in wireless sensor networks

• Main Author: He, Jie.
• Other Authors: Xie Lihua
• Format: Theses and Dissertations
• Language: English
• Published: 2011
• Subjects: DRNTU::Engineering::Electrical and electronic engineering::Wireless communication systems
• Online Access: http://hdl.handle.net/10356/43526
• Institution: Nanyang Technological University

Wireless sensor networks (WSN) connect physical environments with enterprise management and information systems to provide advanced monitoring, automation and control solutions for a range of applications. Since the 1990s, with the advancement in the technologies of wireless communication, embedded computation, sensor and MEMS (Micro-Electro Mechanical Systems) etc., more people have increasingly paid greater attention towards micro sensor and WSN. WSN has great potentials in applications such as target tracking due to sensing, computation and communication capabilities of sensor nodes and the fact that it is easy to deploy sensor nodes. Many researches have been conducted for the field of target tracking. This dissertation researches on algorithms of target tracking using WSN. The basics on WSN and the principle of target tracking are introduced in Chapter 1, Chapter 2 and 3 propose an energy efficient target tracking algorithm. Based on the research of existing target tracking algorithms, this dissertation discusses performances of different algorithms and proposes a target tracking algorithm. This algorithm can balance energy consumption among sensors, so as to extend the network lifetime for more tasks. This dissertation elaborates the connectivity between sensor nodes which are involved in the target tracking process and proposes a solution to the problem of connectivity when the transmission radius is less than twice of sensor radius, so as to reduce the code of transmission. Lastly, in target tracking systems, because of the existence of an external “noise elements” which decreases the accuracy of target tracking dramatically, chapter 4 imports the particle filter algorithm to solve the noisy measurement problem in the sensor network.