Research On Hybrid Optimization Algorithm For Angular Dynamic Experimental Design Of IMU

The inertial system has gradually completed the transition from platform to strapdown.The strapdown inertial navigation system replaces the physical platform with a digital platform,which not only reduces costs but also improves reliability.However,since the Inertial Measurement Unit(IMU)is directly mounted on the body,the accuracy of the system is greatly affected.In this paper,an improved hybrid optimization algorithm is proposed to design an optimal rotation trajectory for the biaxial test turntable to improve the calibration accuracy of the IMU dynamic error coefficient.In the process of establishing the IMU angular dynamic error model,the navigation error equations are first established based on the output error of the IMU,and then the model is simplified according to the characteristics of the ring laser gyro IMU and the micromachined gyro IMU.Then based on the Kalman filter method,it is determined that the trace of the minimized covariance matrix is a preliminary optimization target.Then,based on the characteristics of the turntable,the constraints that need to be met in the problem are determined,and the constraint conditions are processed by the penalty function to determine the final optimization goal.Aiming at the optimization problem in this experiment,among the many optimization random search algorithms,the two methods of pattern search algorithm without derivative information and simulated annealing algorithm with better global search performance are selected,and the principle is studied separately.Two traditional algorithms are used to solve the optimization target.The performance of the two algorithms is compared based on the optimization results.The improved scheme is proposed from three aspects.Finally,a hybrid optimization algorithm combining two algorithms is obtained.The traditional simulated annealing algorithm and the improved hybrid optimization algorithm are used to solve the optimization target in this experiment respectively.Simulate and plot various error coefficient calibration accuracy curves.Compare the estimated values of each error coefficient under the optimization of two algorithms.From the perspective of error accuracy,the calibration accuracy of the dynamic error coefficients of the ring laser gyro IMU is improved by 3%~5%.For the micro-mechanical gyro IMU,the calibration accuracy of the nonlinear error coefficient is improved by 24%~40%,and the calibration accuracy of other dynamic error coefficients is improved by 2%~19%.From the calculation time,compared to the single simulated annealing algorithm with the improved parameters,the time of the hybrid optimization algorithm increased by 5.42%~12.86%.Considering the improvement in accuracy,it is considered that the increase in time is acceptable.It is verified that the improved hybrid optimization algorithm proposed in this paper is a high-performance search algorithm,which can effectively improve the accuracy of error calibration in the IMU angular dynamic calibration experiment.