基于广义互相关理论的风速测量算法研究

Research on arithmetic of wind-metering based on generalized cross correlation

由于超声波时差法测风速对于时间测量要求很高,0.1 m/s速度精度时差Δt仅为400 ns,这就需要很高的采样率和大的系统存储空间。将时差Δt的测量分为"粗测"、"细测"两部分,用插值相关的办法可以有效解决这个问题。插值后通过传统互相关法可准确测量时差Δt的"细测"部分,然而这种方法只有在平稳噪声环境下效果较好,局限性较大,实际测量中结果误差较大。为了克服这问题,通过广义互相关算法(GCC)可提高这部分时差测量的准确性。广义互相关法将回波信号在频域进行加权处理,提高了信号频谱特性,抑制了噪声对测量的影响。实验结果表明,广义互相关算法在白噪声以及有色噪声中都有很好的效果,测量准确性大大提高。

The method of wind speed and direction based on ultrasonic time-difference needed time detect very accurate, when the wind speed is 0.1m/s, the time-difference between two waveforms is only 400ns. This requires a high sampling rate and large system storage space. To solve this problem, it divided the time difference into two parts, ＂coarse detected＂ and ＂fine test＂, then dealt the waveform with interpolation and cross correlation. After the waveforms interpolated, the traditional eross correlation obtained correct difference, but this method had a significant limitation, it worked well only in stationary noise, error results often appeared in actual measurement. In order to overcome this weak point, this paper used the generalized cross correlation （GCC） to realize this part of time-difference detected correctly. With echo signal weighted in the frequency domain, generalized cross correlation improved the spectral characteristies, inhibited the impact of measurement noise. Experimental results show that GCC is well used either in stationary noise or colored noise, improves the measurement accuracy greatly.