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针对捷联惯导(strapdown inertial navigation system,SINS)/全球卫星导航系统(global navigation satellite system,GNSS)紧耦合滤波算法中状态方程线性、观测方程非线性的特点,对超球面单型卡尔曼滤波器(spherical simplex Kalman filter,SSKF)进行了简化:采用普通卡尔曼滤波的状态矢量预测和SSKF的观测值预测及滤波更新完成滤波计算,省去了SSKF状态矢量预测时sigma点生成和对每个sigma点进行状态矢量预测和加权求和的过程,在不损失滤波精度的基础上缩短了滤波计算耗时。经过数学仿真验证,在SINS/GNSS紧耦合中,简化SSKF与SSKF几乎可到达一致的滤波估计精度,而且简化SSKF的计算耗时更短,效率更高。
Aiming at the linearity of the equation of state and the non-linearity of the observation equation in the tightly coupled filtering algorithm of strapdown inertial navigation system (SINS) / global navigation satellite system (GNSS), the hyperspherical single kalman filter (SSKF) is simplified: the state vector prediction using ordinary Kalman filtering and the observation of SSKF prediction and filtering update filtering calculation completed, eliminating the need for SSKF state vector prediction sigma point generation and each sigma point state vector prediction and weighted summation process, without loss of filtering accuracy based on the shortening of the filter time-consuming. After mathematic simulation, SINS / GNSS tight coupling simplifies SSKF and SSKF to achieve almost the same accuracy of filter estimation, and simplifies the calculation of SSKF in a shorter and more efficient.