SAR/INS组合导航系统中，当SAR量测输出时间间隔较长时，惯性导航得不到及时修正，系统将具有较强的非线性特性，导致常规卡尔曼滤波算法的精度受到影响甚至滤波发散. 为了提高组合导航的精度，该文结合惯性导航系统的非线性模型，设计基于无迹卡尔曼滤波(UKF)解决非等间隔量测修正的SAR/INS组合导航非线性滤波算法，并通过协方差分析对比研究常规卡尔曼滤波和该文算法的性能. 仿真结果验证了该文算法具有更高的精度.

The SAR image navigation system is highly nonlinear when it takes long time to output measurement in the SAR integrated navigation system (SAR/INS), and when the inertial navigation error cannot be modified in time. Using conventional Kalman filtering to deal with the nonlinear system, the filter accuracy is affected and even becomes divergent. In order to improve the integrated navigation precision, based on SAR/INS coupled navigation system and the unscented Kalman filtering (UKF), we propose a UKF algorithm for unequal interval problems, and solve problems of information fusion in SAR/INS. Performances of conventional Kalman filtering and the UKF algorithm are studied in simulation analyses of covariance. The result
demonstrates that the method proposed in this paper produces better filtering precision.