一种长航时捷联惯导系统单点综合校正方法

针对长航时捷联惯导系统的误差发散问题,提出一种基于惯性系的单点综合校正方法。采用GPS提供的位置信息和天文导航提供的航向信息构成外观测量。在建立动态误差模型过程中,利用外观测量信息对系数矩阵中的经度、纬度误差及天向失准角进行修正。相对于由惯导系统解算值确定系数矩阵的传统综合校正方法,该方法误差模型中系数矩阵的精度仅由外观测量信息精度决定,不引入惯导系统解算误差。该方法无需对载体运动进行限制,且陀螺常值漂移的估计精度不受校正间隔的影响。仿真结果表明了该方法的有效性。     

Modified robust finite-horizon filter for discrete-time systems with parameter uncertainties and missing measurements

A robust finite-horizon Kalman filter is designed for linear discrete-time systems subject to norm-bounded uncertainties in the modeling parameters and missing measurements. The missing measurements were described by a binary switching sequence satisfying a conditional probability distribution, the commonest cases in engineering, such that the expectation of the measurements could be utilized during the iteration process. To consider the uncertainties in the system model, an upper-bound for the estimation error covariance was obtained since its real value was unaccessible. Our filter scheme is on the basis of minimizing the obtained upper bound where we refer to the deduction of a classic Kalman filter thus calculation of the derivatives are avoided. Simulations are presented to illustrate the effectiveness of the proposed approach.