Self-positioning Algorithm For Sensor Networks Design And Implementation

As the access to information, transmission, and then get the information on three aspects of processing and fusion of sensor network technology, it can through various modular sub-sensors, coordinated to collect all the required amount of information in real time monitoring, sensing and data acquisition. For the collected data, processed by the embedded system, the information processed by the random self-formed network to more than one way to relay the user's terminal.This issue is going to focus on wireless sensor network node self-localization problem. Sensor networks to achieve their position, need to address the following three key issues:1, time synchronization 2, measuring the distance 3, the location calculation algorithm. Which is the positioning of the focus, is also the subject of specific studies will be part of. Achieve a cc2430/31 hardware foundation, zigBee to stack, Rssl the location algorithm for wireless sensor network positioning system. Include the system's overall program, the hardware platform, software platform and operating system structures. RSSI algorithm to improve positioning accuracy for the purpose of detailed analysis of the traditional principles of RSSI location algorithm and positioning process. Ranging and positioning based on its detailed analysis of two stages, pointing out the shortcomings of traditional RsSI algorithm, and proposed two improved methods:First, the introduction of a third party to fix the blind beacon nodes and beacon nodes to measure the distance between nodes; the second is the introduction of the centroid algorithm, combined with trilateration calculation to participate in the blind node position coordinates. Finally, MatLab as a simulation platform, before and after the RSSI algorithm for improving the average error rate for the comparative analysis of the final design process on the subject of the harvest and the results of the study to be summarized.