Research on Multi-Parameter Optimization of Indoor WiFi Positioning Technology - WANG Yingying, CHANG Jun, WU Hao (Ji suan ji gong cheng, 2021)
The existing WiFi-based indoor positioning technology is affected by the number of antennas and channel bandwidth, and has the problems of low positioning accuracy and frequent tracking failures.To address the problem, a multi-parameter indoor passive positioning technology is proposed.Based on the geometric relations, the parameters including Angle of Arrival(AOA), Time of Flight(TOF) and Doppler Frequency Shift(DFS) is explained.Then the parameter model is used to quantify the relationship between user motion and Channel State Information(CSI), simplifying the multi-parameter estimation problem into a maximum likelihood estimation problem. On this basis, the Space Alternating Generalized Expectation Maximization algorithm(SAGE) is used to refine the wrong original parameters to a narrow range, and finally output the target position.Both theory and simulation results show that this method reduces the average positioning error to 0.7 m, providing higher positioning accuracy and stability than existing passive positioning algorithms.