Research On Optimization Of NLOS Error Correction Algorithm Based On UWB TDOA Technology

In more and more large indoor scenes,people are increasingly demanding the positioning of people,objects and target locations.The outdoor positioning technology Global Positioning System(GPS)and Global System for Mobile Communication(GSM)are affected by the building body,and the indoor positioning effect is not obvious.Compared with indoor positioning technologies such as Bluetooth,Radio Frequency Identification(RFID)and Zigbee,UWB positioning technology makes it suitable for indoor positioning technology due to its high transmission rate,high multipath resolution and strong signal anti-interference ability.It has risen and is widely used in military and civilian fields.This topic deeply studies the basic concept,research status and system composition of Ultra-wideband(UWB)positioning technology are deeply studied.The Time Difference of Arrival(TDOA)positioning algorithm in indoor positioning system is studied,at the same time,Angle of Arrival(AOA)positioning algorithm is used as auxiliary positioning algorithm.Aiming at the influence of Non-line-of-sight(NLOS)propagation on positioning accuracy,the Root Mean Square(RMS)delay error model of NLOS error in different indoor environments is given.Finally,the feasibility of Wylie algorithm for identifying NLOS error is verified.Based on the location estimation of TDOA/AOA fusion algorithm by using Chan algorithm,an improved algorithm for iteratively correcting the influence of NLOS error using the steepest descent algorithm(SDA)is proposed to reduce the interference of NLOS error on positioning accuracy.The experimental results show that the proposed improved algorithm can reduce the influence of NLOS error and improve the positioning performance.However,due to the Chan algorithm for initial position estimation,two Weighted Least Squares(WLS)method is used;and the SDA is used for iterative calculation.Multiple iterations increase the complexity of the algorithm.The problem that needs to be solved in the next research work is to reduce the complexity of the algorithm without affecting the positioning accuracy.