Research And Analysis Of Hybrid Positioning Algorithm Based On UWB Signals In Complex Indoor Environments

With the advancement of science and technology and the rise of the concept of Internet of Things,indoor positioning technology has developed rapidly and comprehensively,and the demand for indoor positioning service is getting higher and higher.The positioning accuracy of traditional indoor positioning technologies in a complex and ever-changing indoor environment still can't meet people's increasing need for positioning accuracy.This thesis focuses on a study of hybrid positioning algorithm based on UWB signals and aims to improve the positioning accuracy in NLOS environment.The main contents and achievements of this thesis are as follows:(1)The research background and the domestic and overseas research status of indoor positioning technology are briefly introduced in this thesis.And commonly used indoor positioning methods are introduced.In addition,IEEE 802.15.4a channel model that is used for the 2-10 GHz model is further studied,which contains path loss,power delay profile and small scale fading.And the thesis analyzes the selection of 2PPM-TH-UWB signal in indoor positioning system and introduces the generation of 2PPM-TH-UWB signal.(2)Based on the traditional least square method,this thesis proposes QR decomposition of coefficient matrix and improves TDOA positioning algorithm.Taking the indoor residential environment as the research scene,the thesis compares the performance of the two algorithms with the MATLAB simulation and finds that the LS localization algorithm which is based on QR decomposition not only improves the positioning accuracy but also reduces the running time of the algorithm and improves the immediacy of the positioning system.Furthermore,the NLOS identification algorithm based on TDOA residual weighting is analyzed,and the identification of NLOS errors is simulated under the condition that multiple NLOS errors and different numbers of reference base stations are involved in the location.(3)Under the premise of accurately assessing the path loss exponent in indoor NLOS environments,this thesis draws a conclusion that the ranging based on the RSSI can effectively compensate the errors caused by the NLOS,thereby improving the positioning accuracy in the NLOS environment.In this thesis,the RSSI algorithm based on the least square method and Gauss-Newton iteration algorithm is proposed,and the performance of this algorithm is further simulated and discussed.Also,in the conditions of LOS and NLOS coexisting,the thesis proposes a weighted hybrid algorithm combining TDOA positioning algorithm and RSSI positioning algorithm.Furthermore,by simulating and comparing the positioning performance of the hybrid algorithm and the single algorithm,the superiority of the hybrid algorithm in positioning accuracy is verified.