A New Method For Ambiguity Detection And Baseline Length Resolution Based On Marine Environmen

Marine resources are abundant and vast,and are an important area that countries around the world are striving to develop.Building a seamless positioning,navigation,and timing system spanning the sky,earth,and sea is an important direction in geodesy,which can provide support for ocean exploration and monitoring.Traditional carrier phase based relative positioning technology requires a fixed reference station,while moving relative positioning is more suitable for marine environments and has cost and maintenance advantages.However,there are also some challenges that affect positioning accuracy that need to be addressed,which are different from those on land.This article focuses on the quality control of ambiguity resolution for mobile carriers on the sea,and proposes a new baseline length resolution model combined with wavelet analysis to eliminate the impact of non modeling errors on the baseline resolution results,achieving fast and accurate resolution of the distance between two fixed carriers.The main work of this article is summarized as follows:(1)Detailed introduction to the basic theory of GNSS positioning,including signal structure,pseudo range,and carrier observation equations.The linearization formula of the observation equation was derived,and combined with the differential positioning function model,the linearization form of the differential positioning function model was given.An in-depth analysis and introduction of errors in observation equations were conducted,and the generation method of the original observation random model was introduced.Derived stochastic models for single difference,double difference,multi frequency,and multi system observation equations.Introduced two methods for solving unknown parameters and three methods for estimating integer ambiguity.(2)In response to the problem of traditional ratio test threshold selection relying on experience,the conceptual basis of ambiguity resolution-normalization region-is introduced,and the properties of suboptimal ambiguity are explained.The concept of integer aperture estimation was introduced,and ratio aperture estimation was introduced as a typical representative.The expression of the normalized region for ratio aperture estimation is given,and the geometric configuration of the normalized region for two-dimensional ratio aperture estimation is shown.The key to evaluating the quality of ambiguity resolution using ratio aperture estimation is to select an appropriate threshold to control the fixed failure rate of ambiguity.(3)Propose a method suitable for marine environments that can dynamically determine the ratio test threshold based on model strength.This method is a ratio aperture estimation method based on success rate,failure rate indicators,and ratio test method.Estimate the failure rate through ambiguity degree n and integer least squares,then use Monte Carlo integration to determine the test threshold,and generate a threshold quick reference table.The feasibility of this method has been verified by the experimental results of measured data at sea.Compared with traditional methods,this method performs better in terms of fixed ambiguity rate,fixed accuracy rate,and conditional success rate.In addition,this method can also obtain more accurate positioning results with smaller errors.(4)Introduced the theoretical basis of wavelet analysis.Starting with the definition of wavelet,continuous wavelet transform and Discrete wavelet transform are introduced.Subsequently,the concept of multi resolution analysis,general methods for constructing wavelet bases,and the Mallat pyramid algorithm were discussed in detail.The properties of various wavelet bases were summarized and tables were created for comparison and selection.In addition,this chapter also introduces particularly common wavelet bases in detail,including their function forms,Graph of a function and characteristics.(5)A high-precision solution model with short baseline length for wavelet denoising has been proposed.This model uses the wavelet method of time series analysis to denoise the baseline length time series,thereby weakening the impact of non model errors.Temporal smoothing of denoising results can increase constraint conditions and fully utilize the baseline solution information of each epoch.The new model can obtain baseline length calculation results at millimeter or even submillimeter levels.Compared with the dynamic baseline solution that only performs dynamic baseline solution or only performs dynamic baseline solution with additional time series baseline length constraints,the new model performs better in two precision indicators,namely,Root-mean-square deviation(RMSE)and Standard Deviation(STD).In addition,the accuracy,efficiency,and reliability of baseline length calculation in the new model have been greatly improved,and the convergence time of baseline length calculation has been significantly shortened.