Abstract
Doppler weather radar can detect the changes in precipitation clouds for short-term forecasting. In the process of development of Doppler weather radar and weather identification algorithms, some typical Doppler weather radar base data corresponding to different weather phenomena are necessary for signal processing unit test and algorithm verification. However, the existing real weather radar base data with high quality can't meet the requirement in amount. In this paper, an algorithm based on Deep Convolutional Generative Adversarial Networks (DCGAN) to generate typical weather radar base data is proposed. And in the test signal simulation step, the power spectrum algorithm is improved. The results show that the data produced by the DCGAN have the same characteristics with the real weather radar base data without obvious non-meteorological noise. Moreover, the improved power spectrum algorithm performs better in terms of accuracy rate of the simulation echo signal.
Highlights
Doppler weather radar detects meteorological targets by transmitting microwave that can penetrate cloud and rain
In order to convert the radar base data generated by Deep Convolutional Generative Adversarial Networks (DCGAN) into the radar echo signals without distortion, a new power spectrum algorithm is proposed in this paper, which is referred to as APS
Experiment shows that the DCGAN can generate multiple radar product data simultaneously, including the reflectivity, velocity and spectral width data
Summary
Doppler weather radar detects meteorological targets by transmitting microwave that can penetrate cloud and rain. Doppler weather radar is extensively applied as an important remote sensor for the sounding and short-term forecasting of hazardous weather [1]. The development of high-performance Doppler weather radar and robust weather phenomena identification algorithms are two significant issues. In the stage of development of Doppler weather radar, some echo signals corresponding to different weather phenomena are required as test signals to evaluate the performance of the signal processing unit. The desired echo signals are not always available for application owing to the lack of observable weather events or applicable radar instruments. Echo signal simulation with existing weather radar base data is an alternative we can turn to. In the research process of weather identification based on
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