Research On The Airborne Multi-source Data Fusion Algorithm Based On Beidou

The most critical issue for the aircraft is safe landing,especially in bad weather conditions,if there is no instrument to guide the pilot,it will be impossible to complete a safe landing.When visibility is zero,there will be a more extreme situation where the pilot cannot land the aircraft manually.At present,the aircraft landing approach navigation system at China Civil Aviation Airport is mainly based on the Instrument Landing System(ILS),however,with the development of domestic satellite navigation technology,the defects of the ILS system have become the main reasons for restricting the flight.Therefore,the GBAS Landing System(GLS)was introduced,hoping to solve the problems that occur during the flight of the civil aviation aircraft.This article first elaborates the overall background and significance of multi-source data fusion navigation,and introduces the development history and research results at home and abroad.Then it explains the basic principles of navigation and coordinate system,in addition,the errors of ILS,GLS and INS systems were mainly studied and analyzed.Secondly,the fusion algorithm used in the integrated navigation is introduced,four kinds of fusion algorithms are mainly analyzed,and several algorithms are simulated and compared.Based on the characteristics of the application models,the unscented kalman filtering algorithm is selected.In addition,under the previous theoretical support,the unscented kalman filter is also used to smoothly process the GLS and ILS approach data,besides,the kalman filter fusion algorithm is used to combine the two sets of approach data with the INS data to form more accuracy and higher reliability approach trajectories,and then compares the results of error.In the end,in view of the ILS will be affected by the airspace and the external environment during the approaching and landing process,and then the navigation deviation will occur,affecting the accuracy of navigation during the approach and landing,a model combining ILS and GLS with INS is proposed.Using the improved federal unscented kalman filter algorithm,the difference in the output position is taken as the measured value.Then according to the linear minimum variance criterion,a weighting method according to the optimal coefficient matrix is proposed.Finally,the local navigation data is integrated to obtain the global optimal valuation.Compared with the traditional FKF algorithm,it can effectively reduce the measurement noise,thus improving the horizontal accuracy of the approach and landing guidance.