中文摘要：

针对自主水下航行器（AUV）导航系统对稳定性、精确性和实时性的需求,提出了一种基于改进无迹卡尔曼滤波（UKF）算法的捷联惯性导航系统/多普勒测速仪（SINS/DVL）组合导航新方法。通过分析中低精度组合导航系统的特点和误差模型,在系统的噪声模型为复杂加性噪声时,利用球面分布单形采样变换设计了一种简化UKF组合导航算法。仿真结果表明：与常规的比例对称采样UKF算法相比,在不损失导航系统滤波精度的情况下,基于单形采样变换的简化UKF算法有效降低了系统的计算复杂度,提高了滤波解算效率。

英文摘要：

To meet the stability,precision and real-time performance of navigation system for autonomous underwater vehicle（AUV）,a novel SINS/DVL integrated navigation method based on improved unscented Kalman filter（UKF） algorithm is presented.By analyzing the characteristics and error model of the low-precision integrated navigation system,a simplified UKF integrated navigation algorithm based on spherical simplex sampling transformation is designed for the additive and complex noise model of the system.Simulation results show that this algorithm can effectively reduce the computational complexity and improve the efficiency of the navigation system without loss of filtering accuracy compared with the traditional UKF algorithm using scaled symmetric sampling.