Research On BDS/GNSS Marine Precise Point Positioning Technology And Quality Control Method

With the fast development of the global navigation satellite system(GNSS),especially the Bei Dou navigation satellite system(BDS),BDS/GNSS precise point positioning(PPP)technology has been used in the field of marine positioning widely.Unlike the land,marine surveys not only have a complex environment and many influencing factors,but they also cannot inspect the positioning results through repeated observations or with the aid of the coordinates of existing IGS(International GNSS Service)long-term observation stations.Based on the above situation,the research content of this paper mainly includes quality analysis of marine satellites,Multi-GNSS fast satellite selection methods,baseline constrainted Kalman filtering PPP method,and quality control of marine PPP.The innovations and work include the following aspects.1.This paper sorts out the function model,random model,filtering model,various errors in positioning solution and the corresponding error processing strategies.It also summarizes the current status of GNSS development.These have laid solid theoretical foundation for the subsequent data processing of Multi-GNSS PPP.2.This paper analyzes the signal quality of BDS satellites and GPS satellites in the ocean comprehensively.The research used the 9th Arctic scientific investigation GNSS data of the Xuelong scientific research vessel.Analysis indicators include satellite visible number,geometric accuracy factor,signal-to-noise ratio,multipath effect,and pseudorange noise.The paper studies in detail the quality change law of satellite signals between different types of satellites,different frequency signals and different latitudes.These provide the basis for the setting of subsequent random model and weight of Multi-GNSS for marine PPP.3.This paper proposes an improved particle swarm optimization(IPSO)algorithm,which can solves the problem of Multi-GNSS fast satellite selection in the ocean,thereby improving the efficiency of marine PPP.On one hand,the improved algorithm uses linear inertia weights to balance the local search ability and global search ability of particles in the optimization process.On the other hand,the memory function and automatic adjustment function of immune system are used to ensure the diversity of particle group in the optimization process.Through the improvement of these two aspects,the IPSO can avoid falling into local optimization.Moreover,it can improve the convergence speed as well as the accuracy of the algorithm effectively.The experimental results show that the IPSO is superior in marine Multi-GNSS fast satellite selection.The kinematic marine PPP positioning accuracy of IPSO is better than that of the traditional particle swarm optimization algorithm.4.A method of baseline constrained Kalman filtering PPP is proposed to further improve the accuracy and reliability of positioning in the ocean.Baseline-constrained Kalman filtering PPP and unconstrained Kalman filtering PPP are performed and analyzed in static,pseudo-kinematic,kinematic modes.Compared with unconstrained Kalman filtering PPP,both zero baseline and short baseline constrained Kalman filtering PPP can improve the positional accuracy significantly.Meanwhile,the accuracy improvement degree of short baseline constrainted Kalman filtering PPP is almost equal to that of zero baseline constrainted Kalman filtering PPP.This means that as long as the true value of the baseline length is accurate sufficiently,the short baseline constrainted Kalman filtering PPP is basically equivalent to the zero baseline constrainted Kalman filtering PPP.5.This paper first analyzes the accuracy and convergence speed performance of Multi-GNSS PPP with different combinations.The measured data is based on the globally distributed MGEX(Multi-GNSS EXperiment)stations.Compared with single BDS PPP,Multi-GNSS PPP can accelerate the convergence speed as well as the accuracy of PPP.The more of system combinations number,the higher the positioning accuracy and the faster the convergence speed of PPP.Among different system combinations,C/G/R/E combined PPP has the highest positioning accuracy and the fastest convergence speed.Then this paper uses the method of cross-validation between systems to control the accuracy and reliability of PPP results in static,pseudo-kinematic and kinematic positioning modes.6.An improved isotropy-based protection level method is proposed to assess the accuracy and reliability of marine PPP.The marine measurement environment is complex and the observations are prone to include gross errors,an improved protection level method based on posterior residuals is proposed to evaluate the quality of marine PPP result.The improved isotropybased protection level method based on Receiver Autonomous Integrity Monitoring(RAIM),which adopts median filter to smooth the Euclidean distance of the posterior residual to improve the method performance.Then experiments verify that improved protection level method based on posterior residuals not only can define the level of PPP deviation effectively,but also can reflect the effect of gross errors in observations.