Research On Localization Algorithm Based On Ultra-wideband Technology

In the last decade,with the rapid development and wide application of Internet technology and navigation technology,the demand for high-precision location services has become more and more urgent,and more and more attention is paid to the positioning technology services for complex indoor scenes.positioning system to meet the demand.Traditional indoor positioning solutions are roughly divided into four categories,such as infrared positioning solutions,ultrasonic positioning solutions,Bluetooth positioning solutions and Zig Bee positioning solutions,etc.The above four solutions have different advantages and disadvantages,while Ultra-Wide Band(UWB)positioning technology has good accuracy in complex indoor positioning scenarios due to its high order of magnitude transmission speed,strong penetration capability,low system power consumption,etc.Therefore,this paper proposes to select the ultra-wideband positioning technology as the technical benchmark for the construction of indoor positioning system to achieve the basic functions of indoor positioning.The main aspects are as follows.Based on the existing indoor positioning system scheme,considering the advantages of ultra-wideband positioning technology,the end-to-end distance estimation in the list of modules in the positioning system is proposed using Double-sided Two-way Ranging,and the hardware based on DWM1000 module realizes the ultra-wideband signal transceiving and ranging functions.In the upper computer software,QT is selected to design the positioning algorithm and develop the visualization interface of the system.In the communication of the ranging module,the communication data is transmitted in the form of frames,and the measurement data is analyzed in real time.In order to solve the problem of non-line-of-sight(NLOS)errors encountered in the transmission of ultra-wideband signals,Kalman filter is combined.In order to fully compare the convergence between the distance estimation and the real value,two sets of distance testing experiments were conducted in the same experimental environment to compare the distance estimation expectation and variance under the same ranging method in the two groups,and the results show that the introduction of Kalman iterative filter has good performance in both LOS(Line of Sight)and NLOS environments,and can effectively perform the error filtering in the ranging process with an accuracy range of 10 cm within within the order of 10 cm.The optimization of the localization method is carried out for complex indoor localization scenarios,and the optimal estimation of TOA(Time of Arrival)combined with Chan algorithm is designed,and the strategy of using this method is described.For the positioning scenario with more than three base stations,the TOA-based positioning scheme only does a weighted least squares on the results combined with the Chan algorithm for optimal estimation,which significantly reduces the positioning phase error,improves the system accuracy,and ensures the stable and efficient operation of the positioning system.Finally,the accuracy of the positioning system designed in this thesis is determined by simulating different conditions of signal transmission in the indoor test environment.The antenna delay correction was applied to the ranging module to limit the distance estimation error of the ranging process to about 6 cm,after which the test data were sampled and the positioning results were analyzed.The positioning results show that the positioning accuracy can be optimized to 6 cm in the LOS test environment and 7 cm in the NLOS test environment,and the basic functions of the positioning system operate stably during the experiments,indicating that the hardware module equipment and the software system are built reasonably and efficiently to improve the positioning accuracy effectively.