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针对基于矢量传感器的嵌入式大气数据传感(Flush Air-Data Sensing,FADS)系统速度信号失真问题,提出了一种对引气管路的速度误差和延迟进行补偿的算法。介绍了运用基于矢量传感器的嵌入式大气传感系统测量气流速度的原理,通过差分运算将系统的气动衰减模型降阶成一个简单的二阶状态变量模型,并且通过全模型和降阶模型的频率响应对比实验,证明了降阶模型保留了全模型的大部分动态特性。运用了最小方差估计和卡尔曼滤波理论,针对状态变量模型得到了补偿气动损失的算法。该算法包括飞行后的平滑算法和实时滤波算法。仿真和风洞试验比较和分析了两种算法的性能。
Aiming at the problem of speed signal distortion in FADS based on vector sensor, an algorithm to compensate the speed error and delay of the air bleed line is proposed. This paper introduces the principle of measuring the air velocity by using the embedded sensor system based on the atmospheric pressure sensor. The differential equation reduces the aerodynamic attenuation model of the system to a simple second-order state variable model. In response to comparative experiments, it is proved that the reduced model retains most of the dynamic properties of the whole model. Using the least variance estimation and Kalman filter theory, the algorithm of compensating the aerodynamic losses is obtained for the state variable model. The algorithm includes smoothing algorithm and real-time filtering algorithm after flight. Simulation and wind tunnel tests compare and analyze the performance of the two algorithms.