Development Of An Indoor Target Location And Tracking System Based On Quantitative Data

With the development of technology,locating and tracking technologies have brought great changes to people's lives.For example,GPS has been widely used in military and civilian fields,and has been welcomed by the public.However,because the electromagnetic waves are easily blocked and absorbed by the building,it is impossible to complete accurate indoor positioning.Therefore,the development of high-precision indoor positioning tracking technology is a hot issue in the field of science and technology.This paper firstly conducts a detailed comparative analysis of various positioning methods,including RSSI positioning method,AOA positioning method,TOA positioning method,and TDOA positioning method.It is determined that this subject uses ultra-wideband technology to achieve accurate positioning and tracking of moving targets based on ranging information.Then it introduced three nonlinear filtering target tracking algorithms used in this subject,including EKF algorithm,UKF algorithm,CKF algorithm,and analyzed the principles and advantages of the three tracking algorithms in detail.In the wireless sensor network positioning and tracking system,due to the problem of limited energy and bandwidth of the sensor nodes in the transmission channel,this paper adopts two quantization methods to reduce energy and bandwidth consumption,which are the uniform quantization method and the 1-bit quantization.The distance information measured by the sensor is uniformly quantized at different levels,and combined with different estimation algorithms;a quantitative estimation algorithm with different accuracy can be obtained.The finer the quantization level,the higher the estimation accuracy.In practical applications,the corresponding quantization level can be taken according to the actual accuracy,so as to obtain the purpose of not only saving communication bandwidth but also ensuring estimation accuracy.According to the difference between the distance information measured by the sensor and its one-step forecast value,the new information is generated.By taking the sign of the new information and performing 1-bit quantization,the communication burden can be significantly reduced.Experimental results verify that the two data quantization methods can significantly save node energy and communication bandwidth when the accuracy allows.This topic is developed a multi-base station one label positioning tracking system,in the laboratory to build a hardware platform and software algorithm implementation.In the actual environment,different motion models have been established.The base station encapsulates the measured distance information,adopts the UDP data transmission protocol,and transmits it to the PC-side fusion center through the wireless WIFI module and intermediate router.The receiving end realizes the data reception;data fusion processing and data fusion through QT and MATLAB mixed programming and position trailing result display.In the fusion center,a centralized quantitative observation fusion method is adopted to achieve the positioning and tracking of moving target.The system has been tested and can run normally with an error within a reasonable range.