Design and implementation of an RSSI localization algorithm based on Kalman filter

To solve the problem of inaccurate accuracy and large noise signal of traditional RSSI location algorithm, especially in harsh environment with many obstacles and interference factors, we put forward a design and implementation of RSSI location algorithm based on Kalman filter is presented. Firstly, Kalman filter is used to filter the collected RSSI value signal as a whole to alleviate the problem of signal drift and impact and improve the state accuracy. Finally, an improved weighted quadrilateral ranging positioning algorithm is used to correct the filtered signal again to make the positioning of the nodes to be measured more accurate. The simulation results show that the trajectory after Kalman filtering is closer to the actual trajectory than that before filtering. The algorithm in this paper is compared with the traditional trilateral and quadrilateral ranging positioning algorithm. To a certain extent, the positioning error is smaller and more stable with the increase of the number of experiments.