Things Sensor Node Localization Algorithm

With the rapid development of Internet of Things, the sensor technology has received widespread attention and application, which constitutes the wireless sensor network(WSN) that can connect the physical world to the digital world. The existing research work in the current international will be applied to environment monitoring and protection, the control of Aviation and Aerospace’s placement, localization and tracking of the military targets and to identify and locate the accident sources, etc. In various applications, the location information is critical to the monitor activities of WSN, at the same time, the location information can also be used to improve the routing algorithm so to improve the routing efficiency. In the present applications, the most widely used positioning system is Global Positioning System(GPS),however considering the limitations of network cost and layout, use GPS to locate nodes is extremely extravagant. Therefore, the node localization algorithm has become a key research direction in wireless sensor network.This paper studied Range-based and Range-free these two types of localization algorithm, and discussed their theory and performance. The former via RSSI, TOA, TDOA and AOA to measure the actual distance or orientation between the unknown nodes and the anchor nodes, these algorithms have high positioning accuracy, high cost, complex hardware and the measurement results are vulnerable to the environment impacts. While the latter do not need to directly measure the distance between the unknown nodes and the anchor nodes, have good positioning accuracy, greatly simplified the hardware conditions and have better energy efficiency, thus have been widely studied and applied.Then detailed analysis APIT this traditional Range-free algorithm. Against APIT algorithm’s low coverage rate, proposed an improved algorithm B-APIT and simulated the improved algorithm by MATLAB. The simulation results show that in premise of not reducing APIT algorithm’s positioning accuracy, the improved algorithm effectively improved its localization coverage rate, and the algorithm has good fault tolerance and adaptability.