【摘要】 用于余度捷联惯性测量单元(IMU)的故障检测及分离(FDI)方法的性能受到诸如输入轴不准,刻度因子误差以及偏倚这样的传感器误差的限制。本文采用分离偏倚估计方法以获得上述影响奇偶向量的传感器误差的线性组合的估计,然后将这些估计用于构成补偿的奇偶向量,该奇偶向量不包括传感器误差的影响。用经补偿的奇偶向量代替未经补偿的奇偶向量进行故障检测及分离判决以提高FDI的性能。仿真结果表明奇偶向量补偿算法可大大提高FDI的性能,特别是在飞行器做机动飞行时。更多还原

【Abstract】 The performance of a failure detection and isolation(FDI) algorithm applied to a redundant strapdown inertial measurement unit (IMU) is limited by sensor errors such as input misalignment, scale factor errors, and biases. A separated-bias estimation method is applied to obtain estimates of those combinations of sensor errors that affect the parity vector. These estimates are used to form a compensated parity vector which does not include the effects of sensor errors. The compensated parity vector is then used in place of the un-eompensated parity vector to make FDI decision tor improving FDI performance. The parity vector compensation algorithm will allow the reduction or elimination o! dynamic thresholds, and permit detect;on of soft failure during rapid vehicle maneuvers. In this paper the problem of noise compensation for FDI systems is also presented. Simulation result shows that the parity vector compensation algorithm can significantly improve FDI performance, especially during vehicle maneuvers.更多还原