离心机试验中惯导平台误差系数辨识方法

针对离心机试验中惯导平台误差系数辨识问题,提出一种6位置辨识方案。建立误差系数辨识的非线性模型,再利用扩展卡尔曼滤波估计误差系数。由滤波中的估值方差矩阵计算各误差系数之间的相关系数,用相关系数分析系统的可观性,并将所有相关系数之和最小作为优化指标,利用遗传算法得到最优的位置组合。仿真结果表明,采用该方案可以有效辨识出惯导平台中与加速度高阶项有关的各项误差系数。

Error parameters identification for inertial navigation platform based on centrifuge test

A 6-position identification scheme is developed, in order to identify the error parameters of inertial navigation platform (INS) in the centrifuge testing. The non-linear model of the INS for the identification is established, and the extended Kalman filter (EKF) algorithm is applied to estimate the error parameters. The correlation coefficients among the error parameters calculated with the estimation error covariance matrix in the filter are used to analyze the observability of the system. The optimization criterion is to minimize the sum of all the correlation coefficients, then the genetic algorithm is utilized to obtain the optimal position combination. The simulation results show that the scheme is valid to identify all the coefficients proportional to higher-order acceleration with high precision.