Self-Localization Algorithm In Wireless Sensor Networks

Wireless sensor networks hold the promise of many new applications in the area of monitoring and control. Examples include target tracking, intrusion detection, wildlife habitat monitoring, climate control, and disaster management. Wireless Sensor Networks is integration of sensor techniques, embedded computation, distributed information processing and wireless communication. The underlying technology that drives the emergence of sensor applications is the rapid development in the integration of digital circuitry, which will bring us small, cheap, autonomous sensor nodes in the near future.Since location information is the prerequisite for various applications, self-localization, which is an indispensable supporting technique in WSNs, became the focus of attentions. Self-localization of sensor nodes is to determine the physical coordinates of nodes. The physical limitations of the sensor nodes, however, require unorthodox solutions for many problems. With the innate feature of resource -constraint and energy-constraint, WSNs localization brings a lot of challenges to researchers.In this essay, the principles and characteristics of self-localization techniques are discussed and presented. The criterion of performance evaluation and typical algorithms are also described in detail. The main founding is as follows:Discuss three representative distributed localization algorithms named Ad-hoc positioning, robust positioning and N-hop multilateration. They all meet basic requirements for self-organization, robustness, and energy -efficiency. Fully analysis and comparison are given based on simulation result on a single simulation platform. Recommendations for each algorithm are explained.Bring forth an improved algorithm called RW-DV-Hop by introducing RSSI quantization parameter into original DV-Hop algorithm. Simulation shows the effectiveness of improvement.Conclusions are drawn after tight arguments and prospect for future work is proposed.