Research On Ranging And Indoor Location Algorithm Based On Low Power Nodes

In recent years, with the great development of mobile Internet and intelligent terminal equipment, indoor positioning technology has been absorbed into the people's production and life, becoming an important service, from the global positioning system to provide high precise positioning outdoor to the indoor positioning system in the narrow.seamless connection is constantly to provide people with indoor and outdoor and indoor positioning out of high quality, how to further improve the indoor positioning system has become the focus of current research. Indoor environment is complex and changeable, there are obstacles, random interference, sudden interference and noise interference and other factors, which brings challenges to the research of the indoor location.In this paper, we first study the ranging algorithm based on received signal strength indicator (RSSI). The uncertainty of the indoor environment and the frequent movement of people will cause the big change of the RSSI. Cluster analysis is used to eliminate the short-term burst interface by using the clustering algorithm. Then use the Gaussian filtering or Kalman filtering to eliminates random interface caused by air,temperature and other electronic devices. Finally, the least squares method is used to fit the indoor signal propagation model to calculate the parameter value of the model. In practical application, we put forward the segmentation model of signal propagation model and the dynamic correction of the model.The paper focuses on the indoor location algorithm. Aiming at the shortcomings of low accuracy and poor robustness of the existing localization algorithm, the paper put forward a weighted localization algorithm, which makes full use of the useful information of the nodes in the network and realizes the localization by weighted combination.According to the inevitability of the existence of errors in the process of measurement, the paper presents a fusion of several positioning algorithm of cooperative localization algorithm, firstly using trilateral positioning get the region where the node is located, then calculate the centroid of the region using the weighted centroid localization algorithm, Then according to the Taylor series expansion, doing the Taylor series expansion at the centroid and get the coordinates of the node by cyclic algorithm. Finally, a convex optimal location algorithm is proposed,which transform the localization problem into the convex optimization problem and realizes the localization of nodes. The results in the real environment show that the proposed improved indoor location algorithm improves the positioning accuracy and robustness.Finally, the paper designs and implements an indoor positioning system and verifies the effectiveness of the proposed positioning algorithm and the stability and feasibility of the system.