摘要
红外传感器姿态测量系统具有成本低、体积小、重量轻等优点,但由于大气环境的影响和无人机飞行过程中的噪声干扰使测量得到的姿态角存在较大误差;针对这一问题,采用参数标定和卡尔曼滤波算法理论,结合红外传感器输入输出特性,提出了一种改进方法;通过场地实验获得红外传感器的对地倾角和输出电压的函数关系并对各个参数进行标定;通过推理得到无人机姿态测量算法;采用卡尔曼滤波对红外传感器的输出电压进行滤波去噪来提高测量精度;最后进行了机载飞行实验,将测量的结果与改进前的结果进行对比,精度由原来的±5℃变为±2℃,验证了该改进方法的可行性与正确性。
Infrared sensor attitude measurement system has the advantages of low cost, small size, light weight, but due to the effects＇of atmospheric environment and UAV flight noise, the results have big error. For the consideration of this question, using parameter calibra- tion and Kalman filtering algorithm theory, combined with the input-output characteristics of infrared sensor, an improved method has pro- posed. The relationship between the inclination angle and the output voltage is obtained through the field experiment. After the theoretical derivation the attitude measurement algorithm is put forward. Kalman filter is used to filter the output voltage of the sensor to improve the measurement accuracy. Airborne flight experiments successfully demonstrated the proposed method has the advantages of decreasing the er-ror for attitude angle, and the precision change from ±5℃ to ±2℃.
出处
《计算机测量与控制》
北大核心
2013年第4期883-885,923,共4页
Computer Measurement &Control
关键词
红外传感器
姿态测量
参数标定
卡尔曼滤波
infrared sensor
attitude measurement
parameter calibration
Kalman filtering
