Research Of RFID Indoor Localization Algorithm Based On RSSI

With the rapid development of microelectronics technology, communication technology and computer technology, as an important application of sensor networks, wireless positioning more and more people’s attention, especially in complex indoor environments, the related theory and technology in academia also attracted research boom. In recent years, based on Wi-Fi, ZigBee, RFID technology, such as indoor positioning research was carried out rapidly. In particular, RFID technology, with its advantages of low cost, high accuracy, low latency, non-contact have become the main choice of indoor positioning technology.Based on signal strength(RSSI), this subject Depth analysis of RFID indoor positioning algorithms. Firstly, based on the analysis of indoor positioning technology, several common positioning technology are analyzed and compared, pointed out the features of RFID positioning technology, research the current RFID often used indoor location positioning method, analysis and comparison of the advantages and disadvantages of several positioning method. Then combine the characteristics of this paper, detailed analysis of based on the Distance-Localization algorithm loss model, LANDMARC algorithms, VIRE algorithms, further thinking innovative approach of this paper. According to the characteristics of 2.45 GHz active RFID RSSI to deal with the experimental data, Gauss-Kalman filter was carried out on the RSSI noise filtering, so through data processing to avoid the positioning error caused by the noise, and improves the practicability of the experimental data. Then, based on the analysis of indoor wireless signal propagation model, For the traditional localization algorithm path loss model parameter estimates are not accurate, This paper proposes a RFID- neural network indoor positioning algorithm based on RSSI and distance. In the neural network model, RSSI is input value, Distance as the output value, the new algorithm effectively avoid the path loss model parameters error estimate, improves the positioning accuracy. Finally, with the actual environmental analysis, proposes a RFID- neural network indoor positioning algorithm based on RSSI and Path loss coefficient, RSSI is input value, path loss coefficient as the output value, Improve the accuracy of the positioning environment path loss coefficient of each points, further improve positioning accuracy, and through the theoretical and measured data demonstrate the superiority of the algorithm.