kalman

代码说明：

  在对适用于 ＧＰＳ／ＩＮＳ组合导航非线性模型的容积卡尔曼滤波进行深入研究的基础上，提出了一种改进的多重渐消 Ｈ∞ 鲁棒容积卡尔曼滤波算法．基于系统状态的可观测性给出多重渐消因子矩阵求解过程，提高滤波算法的稳定性，抑制滤波发散；引入 Ｈ∞ 鲁棒思想，构造多重渐消Ｈ∞ 鲁棒容积卡尔曼滤波器；提出采用一种奇异值分解的矩阵分解策略代替标准容积卡尔曼滤波中的 Ｃｈｏｌｅｓｋｙ分解，进一步提高算法的数值稳定性．结果表明：改进的多重渐消 Ｈ∞ 鲁棒容积 算法不仅能有效抑制滤波发散，提高算法的稳定性，还对观测异常值具有更高的鲁棒 性；(Based on the in-depth study of the volume Kalman filter for the nonlinear model of GPS/INS integrated navigation, a new method is proposed. An improved multi-fading H_ infinity robust cubic Kalman filter algorithm is proposed. Based on the observability of the system state, the multi-fading is given.)

文件列表：

kalman, 0 , 2018-09-11
kalman\20326972Achieving_integrity_in_an_INS_GPS_navigation_loop_for_autonomousland_vehicle_applications.rar, 356604 , 2018-09-11
kalman\27796708An-Integration-of-GPS-.rar, 636589 , 2018-09-11
kalman\27796738kalmanfusion.rar, 1685 , 2018-09-11
kalman\41695046Attitude-estimation-.rar, 595028 , 2018-09-11
kalman\77433631An-Integrated-DGPS_IMUh.rar, 155086 , 2018-09-11
kalman\87361018GPS_INS-integration.rar, 395274 , 2018-09-11
kalman\887668140ExtendedKalmanfilteforintegratedglobalpositioning_inertialnavigationsystems.rar, 287347 , 2018-09-11
kalman\89142886INS_GPS_integrated_navigation_system.rar, 3758 , 2018-09-11