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中文摘要：
针对伪距、伪距率紧组合导航精度低、姿态角误差修正误差较大的缺点,从参数可观测性角度提出一种两步自适应Kalman滤波算法。首先简单介绍紧组合Kalman滤波的过程,然后给出两步自适应抗差滤波的公式和具体步骤,并且进行分析和比较。最后用实测算例对提出的算法进行验证。结果表明,相比于伪距、伪距率紧组合Kalman滤波,两步自适应抗差滤波的导航精度受组合周期的长短、INS惯性元件误差的大小影响较小,精度略有提高,更重要的是能够控制动态扰动异常和观测异常的影响,在惯性元件误差较大的情形下也能够很好地估计元件误差,避免姿态角错误修正。
英文摘要：
In tight integrated navigation based on pseudorange and doppler observation,the precision is poor and the modification of the attitude errors is not accurate for poor observation precision of pseudorange.So a two-step adaptive robust Kalman filtering based on the observability of the parameters is presented.First the process of the tight integration is given and then the formulas and the approaches of the new method are deduced and analyzed.Finally an actual calculation is given.It is shown that compared with tight integration,the two-step adaptive robust Kalman filtering can control the disturbances of the state and the outliers of the observation.And the navigation precision does not decrease while the integration period becomes longer and the INS errors become bigger.The INS errors can be rightly estimated and the precision of attitude angles is improved.
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