DEVELOPMENT OF LOCATION ESTIMATION ALGORITHM UTILIZING RSSI FOR LORA POSITIONING SYSTEM

Abstract

LoRa is identified as Long-Range low power network technology for Low Power Wide Area Network (LPWAN) usage. Nowadays, Global Positioning System (GPS) is an important system which is used for location and navigation predominantly used in outdoor but less accurate in indoor environment. Most of LoRa technology have been used on the internet-of-things (ioT) but very few use it as localization system. In this project, a GPS-less solution is proposed where LoRa Positioning System was developed which consists of LoRa transmitter, LoRa transceiver and LoRa receiver. The system has been developed by collecting the RSSI which is then used for the distance estimation. Next, Kalman filter with certain model has been implemented to overcome the effect of multipath fading especially for indoor environment and the trilateration technique is applied to estimate the location of the user. Both distribution estimation results for Line-Of-Sight (LOS) and Non-Line-Of-Sight (NLOS) condition were analyzed. Then, the comparison RMSE achievement is analyzed between the trilateration and with the Kalman Filter. GPS position also were collected as comparison to the LoRa based positioning. Lastly, the Cumulative Density Function (CDF) shows 90% of the localization algorithm error for LOS is lower than 0.82 meters while for NLOS is 1.17 meters.