Research Of Positioning System In Wireless Sensor Network Based On Mixed Filter Algorithm

Wireless sensor network technology has always been one of the topics at the forefront of science and technology. Since the 20th century, it has received significant development and improvement. Because of the association with many other areas of technology, the improvement in these areas of technology also pushes wireless sensor network technology forward. It gains more attention, and more applied to different fields of society. Positioning technology based on wireless sensor network is one of its uses. The development target of this technology is to improve the accuracy, reduce the power consumption.Based on the research of principle of wireless sensor networks positioning, this article propose a positioning algorithm of wireless sensor network based on RSSI positioning algorithm, and combine it with PC software to form a complete positioning system. Before starting positioning work, the article makes sure the values of the model parameter A and n, based on a radio channel model and measurement data. When the system starts working, it uses CC2530 to collect signal strength value and send the data to PC software. The software use a new algorithm mixed by mean filter, Gauss filter, Kalman filter and linear interpolation. With this algorithm, the result of collection can be more accurate. Then, the radio channel model turns the reliable data to the value of notes distance. Finally, it uses triangle centroid algorithm to calculate the position of unknown node. In accordance with the obtained position of unknown node, the motion trail of unknown node will be drawn on the positioning software. The article use Matlab to simulate the above-described algorithm, in order to verify the improvement of accuracy using this algorithm. There are some pictures of software working at the last of the article.According to the Matlab simulation, the proposed algorithm combined with the advantages of each algorithm, can be verified. It has the strong ability of anti-interference, and it is more accuracy compared to other localization algorithms. So, it deserves further study.