采用卡方检验的模糊自适应无迹卡尔曼滤波组合导航算法

针对低成本惯性测量单元精度受载体机动影响大、先验知识难以准确获知的问题,提出一种采用卡方检验的模糊自适应无迹卡尔曼滤波组合导航算法.首先,根据惯性测量单元的基本情况构造系统噪声的粗略模型;然后,引入卡方检验对系统状态模型进行评估,得到相应的卡方检验值;最后,通过预设的模糊逻辑函数和卡方检验值求取系统噪声估计值,得到具有系统噪声统计特性调整的自适应无迹卡尔曼滤波算法.所提出的算法可以克服低成本惯性测量单元难以准确获知先验知识的缺陷.通过SINS/GPS组合导航系统的仿真实例,验证了所提出算法的有效性.

Fuzzy adaptive unscented Kalman filter integrated navigation algorithm using Chi-square test

The system''s error characteristics is hard to be available when the low cost inertial measurement unit(IMU) is used, because the accuracy of this unit will be changed due to the aircraft manoeuvre. To address this problem, a fuzzy adaptive unscented Kalman filter using Chi-square test(CTFA-UKF) is presented for the integrated navigation system. A rough model of system noise statistics is constructed according to the IMU. Then, the system model can be evaluated through the Chi-square test, and the test value can be obtained. Finally, the estimation of system noise statistics can be calculated by the presupposed fuzzy logic function and test value. The CTFA-UKF can overcome the defect of the low cost IMU. To be concrete, an SINS/GPS integrated navigation system is simulated to verify the effectiveness of the proposed algorithm.