在SINS动基座对准中,H_∞滤波算法比Kalman滤波算法具有更好的抗扰动能力。针对H_∞滤波器的参数优化问题,首先在推导H_∞滤波算法鲁棒机理的基础上,分析了滤波参数对系统状态收敛速度和滤波稳定性的影响,然后引入多模型估计理论进一步优化H_∞滤波参数。经过仿真试验,该参数优化方法是提高SINS动基座对准H_∞滤波器估计效果的有效手段。

As for SINS moving-base alignment, H_∞ filtering algorithm has better anti-disturbance capability than Kalman filtering algorithm. In order to optimize H_∞ filtering parameters, the robust mechanism of H_∞ filter was firstly deduced, and the effect of H_∞ initial filtering parameters on convergence rate and estimation stability was analyzed systematically. Then the multiple model estimation theory (MME) was applied to further optimize H_∞ filtering parameters. The simulations have been conducted, and the results illustrate that the parameter optimization algorithm is effective in H_∞ filtering estimation for SINS moving-base alignment.