Processing Of Angular Dynamic Signal In Microwave Landing System

The microwave landing system is one of the common systems for guiding aircraft landing.The safe landing of the aircraft is a concern.During the landing of the aircraft,the ground guidance platform of the microwave landing system continuously sends the guidance angle of the current aircraft to the airborne equipment so that the pilot can adjust the state of the aircraft.This article mainly studies the angular dynamic data processing based on microwave landing system.Firstly,it introduces the development status at home and abroad and the research purpose and significance of this paper.Then introduces the key technology of the microwave landing system and the algorithm theory involved in dynamic data processing.Secondly,the whole block diagram of dynamic data processing is introduced,and the dynamic data is preprocessed.Under the platform of Matlab,the design of the flight path and the smoothing of the trajectory are realized.In this article,three approaching landing routes are designed.In this way,the angular dynamic change data of the aircraft relative to the ground guidance platform is obtained during the flight;when the dynamic data is received,the data is subjected to singular value culling processing;when the diagonal data is systematically identified,the neural network identification is first used,and the model error is not ideal,and then the improved identification algorithm that is the FFRLS is used to identify and to improve its identification accuracy.The standard angular error filter specified by ICAO is introduced and the corresponding system function is analyzed briefly.Thirdly,the principle of Kalman filtering algorithm based on innovation neural network is introduced.Considering the problem of identification accuracy,this article first uses the FFRLS to identify,but after filtering,it is found that the filtering accuracy is not very ideal.Therefore,we improve the algorithm by using Kalman filtering based on innovation neural network under the identification of neural network.BP neural network compensation is also added here to effectively reduce errors caused by model and tracking data in system identification and improve filtering performance.According to the result of data tracking,the Angle error is calculated,and the standard Angle error filter is designed and simulated.Finally,the design of the upper computer interface is briefly introduced,and the combined debugging of Lab Windows/CVI and ISE hardware simulation platform is used to test the static data of the sending and receiving angles,and the simple analysis is performed to verify the correctness of signal processing and reception.