Modulation Model of High Frequency Band Radar Backscatter by the Internal Wave Based on the Third-Order Statistics

Remote Sensing

Xiaoqing Wang¹  Lei Liu²  Pengzhen Chen³  Xin Zhang³  Jinsong Chong³  Xiangzhen Yu⁴ 

[1] Institute of Microelectronics of Chinese Academy of Sciences, Beijing 100029, China;Institute of Spacecraft System Engineering, China Academy of Space Technology, Beijing 100094, China;National Key Laboratory of Science and Technology on Microwave Imaging, Beijing 100190, China;Shanghai Radio Equipment Institute, Shanghai 200090, China;

关键词: radar backscatter;    modulation model;    internal wave;    third-order statistics;    high frequency band radar;   

DOI  :  10.3390/rs9050501

来源: DOAJ

【 摘 要 】

Modulation model of radar backscatters is an important topic in the remote sensing of oceanic internal wave by synthetic aperture radar (SAR). Previous studies related with the modulation models were analyzed mainly based on the hypothesis that ocean surface waves are Gaussian distributed. However, this is not always true for the complicated ocean environment. Research has showed that the measurements are usually larger than the values predicted by modulation models for the high frequency radars (X-band and above). In this paper, a new modulation model was proposed which takes the third-order statistics of the ocean surface into account. It takes the situation into consideration that the surface waves are Non-Gaussian distributed under some conditions. The model can explain the discrepancy between the measurements and the values calculated by the traditional models in theory. Furthermore, it can accurately predict the modulation for the higher frequency band. The model was verified by the experimental measurements recorded in a wind wave tank. Further discussion was made about applicability of this model that it performs better in the prediction of radar backscatter modulation compared with the traditional modulation model for the high frequency band radar or under lager wind speeds.

【 授权许可】

Unknown