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飞行试验测量数据中存在过程噪声和测量噪声,导致飞行数据之间不相容,国内目前常用的输出误差法不适用于耦合严重的直升机飞行数据相容性检验。采用增广卡尔曼滤波方法进行状态估计,大幅度地消除测量值中的误差;再用输出误差法对增广卡尔曼滤波估计的结果进行相容性检验,并将其应用于直升机四阶纵向等效模型辨识中。结果表明:提出的这种方法既解决了单独使用增广卡尔曼滤波进行数据相容性分析时由于初期收敛过程造成的滤波误差问题,又克服了单独使用输入误差法进行数据相容性时需手动修改时间延迟问题和测量值中误差过大时输出误差法无法收敛问题,使得检验效果与计算效率大幅提升。
Flight test measurement data exist process noise and measurement noise, resulting in incompatible flight data, the current output error method commonly used in China is not suitable for coupling serious helicopter flight data consistency test. The augmented Kalman filter is used to estimate the state, and the errors in the measured values are largely eliminated. Then the output error method is used to test the consistency of the augmented Kalman filter, which is applied to the fourth longitudinal Equivalent model identification. The results show that the proposed method not only solves the problem of filtering error due to the initial convergence process when using augmented Kalman filter alone, but also overcomes the data compatibility when using the input error method alone Manually modify the time delay problem and the measured value error is too large when the output error method can not converge, making the test results and computational efficiency increased dramatically.