The Digital Data Processing Of Ocean Atmosphere Detection

Incoherent Doppler wind lidar is currently the only available instrument for wind field measurement in the clear atmosphere. It is capable of obtaining 2D wind field with high spatio-temporal resolution which is essential to numerical weather forecast, atmospheric dynamics and aeronautic security. This paper focuses on the digital data processing of ocean atmosphere detection.By analyzing the lidar backscatters, the noise of signal includes background noise, electronic noise and atmospheric fluctuation and so on. This paper gives the deniosed proposal. For example, by proofreading the signal, we can obtain the distance of detection. This study uses the MTI method to wipe off physical noise. And we choose the appropriate cut-off frequency of filter to wipe off the electronic noise.In order to achieve operational measurement, two digital processing algorithms are applied for the lidar data processing. Firstly, Empirical Mode Decomposition (EMD) analysis is implemented to improve the SNR of laser backscattering signal. Meantime this paper extends the signal and then use EMD method, so we can process the point problem. Secondly, wavelet analysis is used to improve the accuracy of the wind velocity derived from lidar backscattering. The study proposes to use discrete biorthogonal wavelets with a distance-dependent threshold to denoise wind speed that has large dynamic range along the data profile.The study uses the signal processing method synthetically to retrieve the wind field. The result prove those method can improve the accuracy of wind field and preserve the neeny information.