Investigation On Geomagnetic/Gyro Attitude Algorithm Method Of Information Fusion

MISSILES precision-guided control is an important direction of development of thecountries of ammunition, and Attitude Algorithm directly affects the control accuracy，is oneof the key technologies to MISSILES flight control.Based on the geomagnetic/gyro attitudemeasurement mode combinations, geomagnetic gyro information fusion attitude solveralgorithm research, specific research results are as follows:Analysis of the geomagnetic gyro alone attitude measurement problems and their sourcesof error, make use of a combination of information fusion attitude determination algorithm toestimate the redundant information to improve the accuracy of the solution.On the basis of thetheoretical analysis of the attitude information fusion algorithm, combining MISSILESattitude measurement of real-time high dynamic characteristics, focusing on the study of theprinciples and algorithms based on weighted Kalman theory, adaptive weighted fusionalgorithm to establish a mathematical model and error model adaptive Kalman filter.In order to simulate the high dynamic MISSILES flight attitude solver, the paperaccording to the selected sensor parameters and error characteristics, using the existingsix-DOF trajectory model, simulate its attitude information.In studying the adaptive weightedfusion algorithm, according to the sensor error model, under the general conditions of theminimum mean square error to find the optimal way of adaptive weighting factors andgeomagnetic gyro attitude measurement values corresponding to gain closer in the "truevalue" of the fusion results. In the study of adaptive Kalman fusion method based on thestatistical characteristics of its online estimate noise establish solver based gyro attitude errorangle error and geomagnetic observation equation equation of state to suppress output filterdivergence, deduced by observing the value of indirect adaptive filtering gain, making the filter has good convergence properties.Simulation results show that the adaptive Kalman filter fusion algorithm error stability,high accuracy, compared to the adaptive weighted data fusion method better.The researchresults can provide a theoretical basis for MISSILES accurate attitude determination and theproject application.