基于多模型估计的捷联系统动基座对准

SINS in-motion alignment using a multiple model estimator

采用卡尔曼滤波方法进行动基座对准过程中,载体挠曲运动等因素会导致系统噪声、量测噪声的不确定性,即系统参数的不确定性。将多模型估计理论应用于捷联系统动基座对准过程中,可以有效抑制系统不确定性因素的影响。建立了捷联惯导系统误差模型和引入外部位置、速度信息的量测模型,针对对准过程中系统噪声和量测噪声不确定的情况建立了多模型自适应估计器。在同等条件下进行了单一模型对准和利用多模型估计理论进行对准的仿真比较,结果显示:基于多模型估计的对准完成后捷联系统具有更高的导航精度;由此说明,动基座对准过程中,系统参数不确定的情况下,多模型估计器有更好的适用性。

In in-motion alignment using Kalman filter, the system parameter, such as system noise and measure noise is uncertain due to the factors such as carrier flexibility. By applying the multiple-model estimation theory, the influence of system uncertainty can be efficiently restrained. The error model of Strapdown inertial navigation system（SINS） in-motion alignment was established, and the measuring model was also established to integrate position and velocity information. A multiple-model adaptive estimator was established to solve the uncertainty problem of system noise and measure noise. Under the same condition, the alignment simulation and comparison were carried out between using single model and multiple-model estimator. The results prove that the SINS with multiple-model estimator is more precise which show that the multiple-model estimator is more adaptive in in-motion alignment.