Research On Navigation And Positioning Method Based On 3D Map In Urban Environment

GNSS is widely used in positioning and navigation because of the characteristics of applicability in all-weather conditions,high accuracy and low cost.However,the solution is vulnerable in urban area that influenced by obstructed signals and observation noise.In order to obtain high accuracy positioning perormance,quality control and multi-data fusion are the keys.Therefore this thesis first discusses the theories and methods of quality control.For the observation environment imperfect,such as the high intensity observation noise,this thesis proposes a positioning model consisting of GNSS data and 3D map.The performance of the model is investigated in different urban environments and the effectiveness and the stability are demonstrated.Based on the GNSS original observations and the general forms of linear combinations,this thesis illustrates the principles and methods of quality control.According to the urban environmental characteristics,a data preprocessing system is established.The effectiveness and necessity of quality control are verified by theoretical analysis and experiments.The numerical results show that the signal-to-noise ratio reflects the strength of carrier phase and can visually discriminate the data quality.Before quality control and data preprocessing,gross error in the GNSS observation should be detected and eliminated.The multi-path is inversely proportional to the satellite elevation angle,and the multi-path of BDS is different for different types of BDS satellites,including GEO,IGSO and MEO.Clock slip can lead to the failure of the cycle slip detection methods.Under the urban environment,multiple cycle slip detection and reparation methods are used in dynamic measurement.Quality control provides basic support for data processing.Owing to the limitation of conventional GNSS positioning method in urban environment,this thesis integrates the road network and the building framework information of 3D map,and then proposes a multi-system positioning model under the constraint of 3D map.In order to overcome the deficiencies of the Urban Trench method,Static Trench method is proposed to improve the positioning accuracy in urban area.By constructing the geometric constraint of the road network and the signal block threshold of building models,the proposed model can decrease the requirement of necessary observation and increase the probability of NLOS detection and correction.The performance of the proposed model is investigated in different obstructed environment and the effectiveness is demonstrated with various experiments.The numerical results show that geometric constraint of road network can meet the requirement of simple modeling and high efficiency,and can evidently improve the positioning continuity.However,simple model has no significant improvement in positioning accuracy.By resetting the signal discriminating threshold,Static Trench method can markedly ensure the continuity of positioning,and then improve the positioning accuracy.In general,the proposed model improves the positioning continuity and accuracy in urban environment,and can meet the requirement of effectiveness.By cooperating with CORS and high-precision maps,referring to differential positioning algorithm,this thesis proposes an improved M-DGPS method and develops smartphone application.By extracting parameters from original NMEA data which used to construct the coefficient matrix of error equation,the proposed method does not need to compute the coefficient matrix with ephemeris data,therefore reduces the computation load and improves the positioning efficiency.The numerical results show that compared with SPS,DGNSS can improve the positioning accuracy obviously and can meet the requirement of effectiveness and stability.Affected by the difference of mobile GNSS chip,the positioning accuracy needs to be further improved.In general,the smartphone application can meet the requirement of low cost and high positioning accuracy in daily life.