自适应卡尔曼滤波在组合导航中的应用研究

对惯性导航系统（INS）与全球导航系统（GPS）分别进行了具体探讨，对比了两者的优缺点，针对INS／GPS组合导航系统中由于模型不准或因量测噪声的复杂多变造成的发散问题，引入了一种基于输出相关法的自适应卡尔曼滤波技术。通过在自适应滤波算法中推算最优稳态增益来调整量测噪声，抑制滤波器的发散，为GPS／INS组合导航系统实现高精度导航提供了有效的途径。仿真结果表明该算法能很好地对系统状态进行最优估计并适应系统噪声的变化，具有比常规卡尔曼滤波更高的导航精度。

Study of Application of Adaptive Kalman Filter Technology in Integrated Navigation System

The GPS and INS are separately discussed in the paper, and comparisons of their advantages and disadvantages are made in the paper. The measurement noise in the INS/GPS integrated navigation system is complex and variable, and the model is inaccuracy sometimes, which could bring divergence. To solve this problem,presents the technology of adaptive Kalman filter based on relative output method. By calculating the optimum static-state gain in the adaptive Kalman filter algorithm to adjust the measurement noise, the technology could restrain the divergence and provide an effective way to realize high precision navigation for GPS/INS integrated navigation system. The simulation results indicate that this filtering algorithm can get a better result in system states optimization estimation. Simul- taneously it has a superiority of adapting system noise variation and this algorithm has better navigation accuracy than the regular Kalman filter algorithm.