| The Beidou Navigation Satellite System(BDS)is a global positioning system independently developed and operated by China.With the development of navigation technology,positioning accuracy is required more and more.In the process of positioning,the elimination of multipath effect,the detection and repair of cycle slip,and the attitude Angle solution in the process of dynamic positioning are the important technical supports for high precision positioning.In order to realize the high-precision positioning of the Beidou system,the specific research contents of this dissertation are as follows:(1)In order to eliminate the influence of multipath effect on positioning accuracy,this dissertation adopts the post-processing method of data.First,the least square method is used to iterate the initial position,and the improved Kalman filtering algorithm is adopted to filter the system noise and measurement noise.Then,the L-M optimization algorithm is used to ensure the global convergence,and the covariance matrix is optimized to obtain a faster and more accurate positioning.(2)The failure of receiver counting due to signal shielding will cause the phenomenon of cycle slip.In order to solve the problem of cycle slip in the localization process,this dissertation proposes a method of using wavelet transform combined with bilinear interpolation to realize cycle slip detection and repair of double difference model.Wavelet transform is used to decompose the high frequency coefficients to obtain the position of cycle slip.Then,the singular values at the cycle slip are replaced by bilinear interpolation method and cycle slip repair is carried out.In this dissertation,two-scale decomposition of the high frequency coefficients is carried out,and the singular values of the high frequency coefficients of the first layer and the first-second layers are respectively replaced to compare the repair efficiency of cycle slip.The results show that the restoration efficiency of the latter method is higher.(3)In the process of dynamic positioning,an adaptive Kalman filter algorithm with improved Allan variance is proposed in this dissertation to solve the problem that the attitude Angle solution is easy to diverge due to the low precision of low-cost inertial navigation system.Before filtering,the complementary filtering of the quaternion improved PID is used to fuse the data to suppress the fluctuation of the data and speed up the operation rate.When the noise is analyzed,the Allan variance analysis method and Gauss-Newton optimization algorithm are used to improve the accuracy of attitude solution,and the attitude Angle can be stabilized in a short time and tracked accurately in a long time. |
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