分形噪声和白噪声是影响光电跟踪系统惯性传感器输出信号精度的重要因素,采用传统的方法很难滤除分形噪声。利用分形噪声在小波变换域的特殊性质,采用小波滤波方式,并在此基础上,实现两种不同带宽的惯性传感器信号的融合。通过将阈值计算进行简化,并对信号输入延拓方式进行改进,提高了信号处理的精度,由此可以大大降低信号的小波变换长度以提高运算速度,最终在相应硬件的基础上实现信号的实时处理。最后的实验验证了该算法的有效性和实时性。

In electro-optical tracking system,fractal noises and white noises have main effects on the precision of inertial sensors,and it is difficult to filter fractal noises by traditional methods.Because of special properties of fractal noises in wavelet transform domain,denoising means with wavelet transform are adopted and data fusion of sensors is implemented.By simplifying the thresholds computation and mending the symmetric extension for signals input,the processing precision is improved and calculation length for signal is reduced greatly.Therefore,the signal can be processed in real time.Some experiments for inertial sensors are carried out and the experimental results verify that the algorithm is valid and real-time.