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中文摘要：
针对标准粒子滤波算法中存在的重要性密度函数难以选取的问题,提出了一种新的迭代平方根容积粒子滤波（ISCPF）算法.将高斯-牛顿迭代和平方根容积卡尔曼滤波（SCKF）算法相结合,得到迭代平方根容积卡尔曼滤波（ISCKF）算法.利用ISCKF算法获得粒子滤波算法的重要性密度函数,有效抑制了粒子退化现象.捷联惯导系统大方位失准角初始对准的仿真结果表明：该算法对航向失准角的估计精度可以达到2.21′,相比于标准粒子滤波（PF）算法和容积粒子滤波算法（CPF）具有更高的估计精度.
英文摘要：
In view of the open question that importance density function of the standard particle filter algorithm is difficult to select,a new algorithm of the iterated square root cubature particle filter（ISCPF）was proposed.Gauss-Newton iteration and square root cubature Kalman filter（SCKF）algorithm were combined to obtain iterated square root cubature Kalman filter（ISCKF）algorithm.The importance density function of PF was obtained by ISCKF algorithm and particle degradation problem was effectively solved.By the computer simulation results,estimation precision of heading misalignment angle can be within 2.21′,and the filtering accuracy of ISCPF is higher than PF and the CPF.
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