基于动态规划算法(DPA)提出一种分析植被弱散射分量的方法。首先,通过改进的密歇根模型(MIMICS)得到水稻的散射分量组成,输出结果与同步陆基散射实验数据以及国外多名学者在合成孔径雷达(SAR)实验中一致;然后,将动态规划算法结合入射角与极化信息建立多维状态向量和递推决策,弱散射分量的叠加在动态规划算法中实现了应用,因此下垫面的类型可以被有效提取;最后,通过实验数据对结果进行比较分析,结果验证了该方法的有效性。

Based on dynamic programming algorithm (DPA) , a new method is proposed to analyze the minor scattering from underlying surface which covered vegetation. First, the backscattering components of vegetation are given using the Michigan microwave canopy scattering ( MIMICS) , and the output of MIMICS is consistent with the conclusion of other scholars in the synthetic aperture radar ( SAR) experiments. Then, constructed in the DPA, the multidimensional sequence state and recursive strategy are derived from the incident angle and polarization. The accumulation of minor scattering is used in the DPA, thus, the water in the underlying surface can be effectively distinguished. Finally, series field experiments are carried out and the observation is used for validation.

TN957. 52

国家自然科学基金资助项目(No. 41571333;No.41371340)