Study On Spatial Combined Location Based On UWB/SINS

In recent years,with the rapid development of the new generation of Internet of Things technology and information technology,the demand for high-precision positioning services in areas such as transportation,public safety,and smart cities is increasing day by day.In automatic driving,when the vehicle is traveling in a heavily shaded environment,high-precision positioning schemes are required to achieve full range positioning to ensure the safety and location information of the driver;In the face of complex large indoor environments in unmanned storage and transportation,existing positioning technologies have problems such as low positioning accuracy and high system deployment costs.However,various positioning technologies have their own advantages and disadvantages,and it is difficult to rely on a single positioning technology to solve these problems.Therefore,this article analyzes and summarizes the characteristics of emerging positioning technologies in detail,selecting ultra-wideband technology and inertial navigation technology,relying on the idea of multi-sensor information fusion,It is proposed to combine ultra wideband technology with inertial navigation technology to achieve complementary advantages of the two positioning technologies to improve positioning accuracy,reduce the cost of positioning system deployment,and provide a new solution for high-precision positioning methods.The main work of this article is as follows:(1)The positioning performance of traditional UWB positioning algorithms is studied.Through simulation experiments,the positioning performance of traditional algorithms in different base station numbers and different noise environments is compared,verifying that Chan algorithm performs best in Gaussian white noise environments,and Taylor algorithm performs best in non Gaussian white noise environments.On this basis,an improved Chan-Taylor particle swarm optimization algorithm(CT-PSO algorithm)based on Chan-Taylor collaborative algorithm is proposed,and simulation experiments are designed to verify the feasibility of the algorithm.(2)Aiming at the lack of commonly used base station deployment schemes for UWB positioning,the spatial deployment of the base station for this positioning method was studied,six deployment schemes with different number of base stations were proposed,and an experimental platform was built to conduct static multi-point fixed point and dynamic positioning accuracy testing experiments.The results show that under the isosceles trapezoidal deployment scheme of five base stations,the positioning accuracy of UWB is optimal,and the positioning accuracy of CT-PSO algorithm in static experiments is 0.168 m,which is 50% higher than that of the trilateral positioning algorithm;In dynamic experiments,the positioning accuracy is 0.186 m,which is 47%higher than the positioning accuracy of the trilateral positioning algorithm,and can meet the needs of high-precision positioning.(3)In order to achieve a high precision UWB/SINS combined positioning method and solve the problem of UWB positioning accuracy degradation in NLOS environments and SINS continuously accumulating errors over time,a combined positioning method based on UWB/SINS extended Kalman filter(EKF)and unscented Kalman filter(UKF)was studied.Through simulation experiments,the performance of EKF and UKF was compared,and then a CT-PSO-UKF algorithm based on unscented Kalman filter structure was proposed.Establish an experimental platform and design a comparative test of positioning performance of UWB,SINS,EKF,UKF,and CT-PSO-UKF under different motion speeds of the object to be tested.The experimental results show that the positioning accuracy of the CT-PSO-UKF algorithm can reach 0.2329 m under the motion state of 0.5m/s,and the accuracy is improved by 0.1085m;In the NLOS environment,the positioning accuracy can reach 0.509 m with a motion speed of 2m/s,and the accuracy is improved by 0.212 m.Experiments have shown that the CT-PSO-UKF algorithm based on UWB/SINS combined positioning has a positive effect on reducing NLOS interference,reducing accumulated errors,and improving positioning accuracy.