Research And Implementation On High Accuracy Carrier Phase Positioning In Urban Area

The satellite positioning and navigation system has greatly changed the lifestyle of human beings since its born.The diversified location based services and applications have become an indispensable part of people's daily lives.The standard single-point positioning with 3 to 5 meters accuracy has been unable to satisfy the high-precision positioning need of modern intelligent equipment.Positioning technology based on carrier phase observation like RTK and PPP has greatly expand the application field of global positioning and navigation system.Those technology can provide up to millimeter accuracy anywhere around the world to surveying and mapping,automatic driving,precision agriculture,deformation monitoring and so on.With the development of new intelligent equipment,such as urban intelligent logistics,UAV distribution,automatic driving,intelligent robots and so on,the demand for high-precision location information in urban environment is increasing day by day.However,in urban environment,the carrier phase precise positioning is still facing the following problems:data preprocessing under urban communication interfere and sparse observation condition,real-time high-precision estimation of floating ambiguity for complex moving carrier,the decorrelation of integer ambiguity resolution matrix for strong space correlated data.And those problem have become one of the hotspots of key technology research in this fieldIn this paper,the theoretical models and methods of carrier phase positioning,such as RTK and PPP,are studied in depth.In order to improve the convergence rate of integer ambiguity resolution in carrier phase positioning,three key problems closely related to integer ambiguity resolution speed are focused on:data preprocessing and cycle slip detection,floating point solution estimation and matrix decorrelation.A cycle slips detection model based on complementary symmetric geometrically free combination,an RTK float ambiguity estimation method based on IMU and n-dimensional LLL reduction algorithm are proposed,which improve the convergence speed of fixed solution effectively.The main contents and innovations of this paper are as follows:1.Aiming at the problem of effective cycle slip detection under the condition of common-band interference and sparse observation on urban area,this paper proposed a symmetrical geometrically free combination to compensate the blind spot by analyzing the mechanism of blind spot in traditional cycle slip detection algorithm and then establishes a second-order differential complementary cycle slip detection algorithm based on the proposed combination.The simulation results show that the proposed algorithm can detect and repair the cycle slip with no detection blind spot when dealing with the observation of 30s epoch interval and the success detection rate is 99.3%,which is better than the TurboEdit algorithm2.Aiming at the problem of low integer ambiguity search efficiency and success rate brought by the low floating-point solution estimation accuracy under complex dynamic conditions in urban applications,this paper introduces Doppler observation and inertial measurement data to model the violent variable speed and acceleration of moving vehicles.A dual feed-back fused attitude and floating-point solution estimation method is proposed for moving vehicles under high dynamic.By establishing the dual feed-back inter-correction model between inertial measurement unit and carrier phase observation,the proposed model improves the accuracy of traditional dynamic model estimation in which the attitude and position are estimated separately.Experiments show that the float-point estimation accuracy of the proposed algorithm under 10 g acceleration is 0.56 meter,which is significantly improved than the traditional tightly coupled model.3.The deterioration of visible satellite distribution caused by building occlusion in urban area will lead to the increase of correlation between positioning equations which will affect of solving efficiency.The decorrelation transformation used by traditional integer ambiguity resolution algorithm utilizes two-dimensional constraint which is difficult to meet the decorrelation need of ambiguity efficient solution in urban applications.This paper establishes a decorrelation transformation model based on lattice basis reduction,which expands the constraint dimension of decorrelation algorithm by using lattice theory method.And then this paper proposes an N-dimensional Lovsz constraint reduced basis and corresponding lattice reduction algorithm,which improves the performance of decorrelation transformation.The simulation results show that for the application of integer ambiguity resolution in RTK and PPP location,the performance of the proposed algorithm is improved by 39%on average compared with the traditional 2-D constraint algorithm.4.By utilizing the methods proposed in this paper,a experiment receiver board based on embedded system is developed.The design is based on the basic framework of open source carrier phase positioning software and uses the cycle slip detection and decorrelation part are reconstructed using the proposed algorithm.The positioning test results under urban area shows that the convergence time,the fix rate and the positioning accuracy is improved by 14%,20%and 12.3%in urban applications.