An indoor positioning system based on WiFi - Zhong, Ziyi (2019)
Although outdoor positioning has been successful in all walks of life with the utilization of the Global Positioning System (GPS), indoor positioning remains an enormous challenge, due to complex indoor environments. To develop an indoor positioning system with high accuracy and low cost, we designed a positioning system based on WiFi. The positioning system can estimate the number and location of fixed transmitters. Fingerprint positioning based on K-Nearest Neighbour (KNN), trilateration positioning and nearest neighbor method are adopted for selecting an appropriate positioning method. In the simulations, it can be found that each of the three methods has both advantages and disadvantages. The workloads and costs of the nearest neighbor method are the minima among the three approaches, while it only provides an approximate location. In contrast, the accuracy of trilateration positioning is best, reaching 0.27m. However, it is dependent on the number of communication devices. Fingerprint positioning can achieve an accuracy of 2.08m, but it is tedious to implement due to heavy workloads. Also, it will become useless as the environment changes. In terms of costs and accuracy, trilateration positioning is the best choice. The moving trail can be obtained by continuously positioning. Kalman filtering is applied to process the moving trail and make it close to the real path with an improved accuracy between 30% and 50%.