Research On The Data Processing Of Magnetic Anomaly Detection Based On Kalman Filter

In the field of non-acoustic detection technology represented by magnetism,light,and gravity,magnetic anomaly detection technology is receiving more and more attention.Powerful countries in the world have invested a lot of resources in research and achieved certain achievements.Magnetic anomaly detection has the characteristics of continuous detection,wide search range,high efficiency,simple and reliable use,fast response,high positioning accuracy,good concealment,etc.On the other hand,it is not affected by environmental factors such as astronomy,meteorology and water ripple.In the research of magnetic anomaly detection,there are problems of how to obtain high-precision magnetic anomaly data and how to deal with magnetic anomaly data.These two problems have hindered the development of magnetic anomaly detection technology,especially the study of magnetic anomaly localization to a certain extent.The purpose of exploring the application of Kalman filtering in magnetic anomaly detection is to obtain more ideal data than traditional numerical filtering methods through the advantages of real-time estimation of Kalman filtering,and to provide excellent data protection for subsequent research work such as magnetic anomaly localization.The thesis has introduced the relevant theories of magnetic anomaly detection technology.This paper not only has explained the reasons for the occurrence of magnetic anomalies and the principle of magnetic anomaly detection,but also it has introduced the magnetic dipole theory,which has an important position in magnetic research.The magnetic dipole theory is combined with the theory Anomaly gradient location algorithm formula.Subsequently,several data processing algorithms for magnetic anomaly detection are described.Among them,the principle of Kalman filter algorithm is mainly discussed,and Kalman filter modeling and simulation is performed on common magnetic anomaly signal data.The wavelet transform and empirical mode decomposition method are briefly introduced.Because the occurrence of magnetic anomalies depends on the existence of magnetic sources,based on the theory,in order to obtain the magnetic field intensity distribution of the target,the magnetic source target(coil)is modeled and analyzed in the laboratory environment.The thesis has designed a relatively complete magnetic anomaly data acquisition system.After comparing the performance of various magnetic sensors and their operating characteristics,a tunnel magneto resistive sensor has been selected as the core sensor of the magnetic anomaly detection system,and a data acquisition circuit has been designed.After that,the Lab VIEW host computer program,Kalman filter algorithm program,and magnetic anomaly location algorithm program used with the acquisition circuit have been written in this subject.In order to verify the working performance of the detection system designed in this paper,the related experiments are designed to verify whether the system can meet the requirements of use.Finally,a magnetic sensor array distributed magnetic anomaly detection and positioning experiment has been designed.The data processing method and the magnetic anomaly gradient location algorithm have solved the position information of the target.