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Research On Geomagnetic Information Processing And Matched Navigation Algorithms

Posted on:2020-02-24Degree:MasterType:Thesis
Country:ChinaCandidate:C Y WangFull Text:PDF
GTID:2370330626953419Subject:Control theory and control engineering
Abstract/Summary:PDF Full Text Request
With the development of geomagnetic measurement technology and geomagnetic matching theory,geomagnetic navigation has gradually become a hot research topic.Geomagnetism includes a variety of matched characteristic information,such as total magnetic field intensity,horizontal magnetic field intensity,magnetic declivity,magnetic inclination Angle,etc.Geomagnetism navigation has the advantages of strong concealment,all-weather,good environmental adaptability and non-accumulation of errors over time.Combined with inertial navigation,the geomagnetic navigation system can help solve the position error divergence problem of the inertial navigation system and meet the navigation requirements of the satellite in the unusable environment.In this paper,the related problems in geomagnetic matching are studied,and the following work is mainly completed:(1)The error correction technology in geomagnetic data detection is studied.Geomagnetic field belongs to weak magnetic field.When using magnetic sensor to measure data,it is easy to be disturbed by external environment.Preprocessing magnetic sensor data is one of the important links of geomagnetic navigation.The error sources in the manufacture and measurement of three-axis magnetic sensor are analyzed,and the comprehensive error model of magnetic sensor is established.Based on the error model,the error analysis model is established,and the error compensation technology of iterative least squares magnetic sensor with forgetting factor is studied,which improves the accuracy of magnetic measurement data and satisfies the navigation requirements.(2)The interpolation and extension techniques in the construction of geomagnetic maps are studied.Various interpolation techniques are analyzed and compared.Through simulation and comparison,Kriging interpolation method is selected.The overall accuracy of Kriging interpolation method can meet the requirements of navigation for reference geomagnetic map.The problem of geomagnetic field continuation in frequency domain is studied.The filtering characteristics of operators in frequency domain are analyzed by mathematical deduction.Fourier transform algorithm is used to deal with the problem of upward continuation,and iterative algorithm is used to solve the problem of unstable downward continuation.The simulation results show that the iterative algorithm has good continuation effect.(3)The problem of geomagnetic matching location is studied from the angle of intelligent optimization.According to the principle of matching correlation of geomagnetic field and based on geomagnetic affine model,a constrained particle swarm optimization algorithm based on population diversity is proposed to overcome the shortcomings of basic geomagnetic matching algorithm such as sensitivity to initial position error and heading error of carrier.The effectiveness and anti-noise simulation results show that the algorithm can effectively correct the INS indication trajectory error and achieve more accurate matching and positioning.?(4)The off-line sports car experiment based on geomagnetic matching navigation system is studied and designed.Vehicle loaded with three-axis magnetic sensor and high precision GPS/INS integrated navigation system SPAN-CPT,using the trajectory provided by the integrated navigation system as the real path,the geomagnetic matching datum map is obtained by interpolation of magnetic sensor measurement data,and the off-line simulation of the geomagnetic measurement sequence acquired by magnetic sensor verifies the error iteration algorithm of magnetic sensor,Kriging interpolation algorithm and the proposed method.The effectiveness of the geomagnetic matching algorithm.
Keywords/Search Tags:Geomagnetic navigation, error compensation, interpolation continuation, particle swarm optimization, matching algorithm
PDF Full Text Request
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