Design Of Lora-based Vehicle Positioning System Applied To Underground Parking Lots

With the development of the economy,the number of private cars is increasing,and underground parking lots in various social places are becoming more and more popular.However,large underground parking lots often have problems such as complicated terrain,unclear lines,difficult to find empty parking spaces,and difficulty in finding a reverse car.These seriously affect the user experience and the efficiency of parking lots.Generally,ground parking lots have relatively mature positioning and navigation systems,and most of them are integrated with the Global Positioning System.However,in the complex indoor environment,GPS signals cannot be received effectively enough,and GPS technology cannot be used.The existing mainstream indoor positioning technologies,such as ultrasonic,infrared,bluetooth,WI-FI and ZigBee,have their own shortcomings.In view of the special environment of underground parking lots,this paper designs a vehicle positioning system based on LoRa in underground parking lots,taking advantage of LoRa's advantages in anti-interference,low power consumption and low cost.In the environment of underground parking lots,the radio signal is easily interfered by the environment in the transmission process,and the RSSI value has a large fluctuation.This paper proposes a method combining gaussian filtering and limited-amplitude filtering to preprocess the RSSI.Compared with the single filtering method,this method has a better processing effect.The RSSI ranging model based on BP neural network is established.Compared with the traditional logarithmic distance loss model,this model avoids the estimation of parameters and reduces the accumulation of errors.Combined with the special communication environment of the underground parking lots,the time delay model of NLOS in theTOA ranging model was analyzed.The limited-amplitude filtering algorithm and the kalman filtering algorithm were combined to filter the sudden NLOS time delay,and the regular NLOS time delay and node module processing error were suppressed by the method of parameter fitting.The ranging characteristics of RSSI technology and TOA technology are analyzed,and the ranging method based on RSSI in the short distance and TOA in the longer distance is put forward.On the basis of ranging,weighted centroid location algorithm is used to calculate the coordinates of label nodes,which improves the adaptability and positioning accuracy of the system.The hardware and software of the positioning system are designed.The hardware part of the positioning system consists of three parts: minimum system module,input and output module and radio frequency module.In the software part,the software has completed the preparation of the location algorithms,anchor nodes,and tag node function programs.The system is applied in actual environment and the feasibility of the system is verified.