CAJ | 학술논문

极化干涉SAR是一种集极化和干涉SAR优势于一体的新型遥感技术.结合两层植被随机体散射模型和极化分解技术,基于极化干涉SAR数据的概率分布统计特征,提出一种利用参数迭代求解预测模璎和测量值最小似然距离的植被高度反演方法.该方法克服了传统最大似然估计方法需已知地表散射特征参数的约束,减少了计算复杂性.最后通过极化干涉SAR仿真数据实验分析,文中算法相对于三阶段反演算法提高了植被高度估计的精度.验证了算法的有效性.
겁화간섭SAR시일충집겁화화간섭SAR우세우일체적신형요감기술.결합량층식피수궤체산사모형화겁화분해기술,기우겁화간섭SAR수거적개솔분포통계특정,제출일충이용삼수질대구해예측모영화측량치최소사연거리적식피고도반연방법.해방법극복료전통최대사연고계방법수이지지표산사특정삼수적약속,감소료계산복잡성.최후통과겁화간섭SAR방진수거실험분석,문중산법상대우삼계단반연산법제고료식피고도고계적정도.험증료산법적유효성.
Polarimetric interferometrie SAR (PolInSAR) is a new type remote sensing technique which combines the advantage of polarimetric SAR and interferometric SAR. Combining the two layer random volume over ground model with the classification of the polarimetric data and from the statistical distribution characteristic of the PolInSAR data, this paper proposes an inversion algorithm of vegetation heights estimation which makes use of the parameters iteration to minimize the hkelihood distance between the model forecast and the sensors observations. The proposed algorithm can overcome the restriction of traditional maximum likelihood esti-mation method which requires the parameters of ground scattering to be known, and also decreases the complexity of calculation. Finally, by analysis of height inversion for the PolInSAR simulated data, the proposed algorithm has better performance than the three stage method, therefore the validity of this method is proved.