School of Automation, Beijing Institute of Technology, Beijing 100081, China.
School of Automation, Beijing Information Science and Technology University, Beijing 100192, China.
Sensors (Basel). 2019 Dec 30;20(1):200. doi: 10.3390/s20010200.
The real-time measurement of the projectile attitude is the key to realize the whole process guidance of the projectile. Due to the high dynamic characteristics of the projectile motion, the attitude measurement is affected by the real-time and accuracy of the gyro signal de-noising. For the nonlinear discontinuity of the conventional extension method in real-time wavelet de-noising, a function extension real-time wavelet de-noising method is proposed in this paper. In this method, a prediction model of gyro signal is established based on the Roggla formula. According to the model, the signal is fitted in the sliding window, and the signal of the same length is predicted to realize the right boundary extension. The simulation and experiment results show that compared with the traditional extension method, the proposed method can in-crease the signal-to-noise ratio (SNR) and the smoothness, and can decrease the attitude mean absolute error (AMAE) and the attitude root mean square error (ARMSE). Moreover, the time delay caused by signal de-noising can be effectively solved. The real-time performance of the attitude measurement can be ensured.
弹丸姿态实时测量是实现弹丸全程制导的关键。由于弹丸运动的高动态特性，姿态测量受到陀螺信号实时性和去噪准确性的影响。针对传统扩展方法在实时小波去噪中存在的非线性不连续问题，本文提出了一种基于 Roggla 公式的函数扩展实时小波去噪方法。该方法基于 Roggla 公式建立了陀螺信号的预测模型，根据模型在滑动窗口中对信号进行拟合，预测出相同长度的信号，实现了右边界的扩展。仿真和实验结果表明，与传统扩展方法相比，该方法可以提高信噪比（SNR）和光滑度，降低姿态平均绝对误差（AMAE）和姿态均方根误差（ARMSE），同时能有效解决信号去噪带来的时延问题，保证姿态测量的实时性。
