The Optimization of RSSI-Neural Network Positioning Algorithm

Abstract

This paper optimized the RSSI neural network positioning algorithm. In-depth analysis of the principles of the Kalman filter and using the Kalman filter to filter the Received Signal Strength Indicator (RSSI) value. Analysis the structure of back propagation neural network and optimized the structure of the RSSI-neural network algorithm. MATLAB simulation verified the optimization algorithm has higher accuracy and more robustness.