This paper presents a new interferometric coherence optimisation approach based on the flower pollination algorithm, called flower pollination interferometric coherence optimisation (FPICO). FPA is a newly developed algorithm based on the pollination process of plants that is used to solve constrained and/or multiobjective optimisation problems. The proposed approach gives us the possibility to control the scattering vectors to be optimised by setting one of its appropriate parameters beforehand. Moreover, the optimised vectors are conforming to the scattering parametrisation, in contrast to previous coherence optimisation methods that are based on eigenvalues problem. Comparisons of FPICO with classical optimisation approaches have shown that the residue rate decreases by more than 70%, which leads to less deformation in the interferometric phase. Furthermore by the enhancement of the phase quality, the results are interesting and provide additional possibilities in contrast to the classical methods such as the optimization of a specific scattering mechanism which may help in scattering decomposition.

本文提出了一种基于花授粉算法的干涉相干优化新方法，称为花授粉干涉相干优化（FPICO）。FPA是一种基于植物授粉过程的新开发算法，可用于解决约束和/或多目标优化问题。所提出的方法使我们有可能通过预先设置其适当参数之一来控制要优化的散射矢量。而且，与先前的基于特征值问题的相干优化方法相比，优化的矢量符合散射参数。FPICO与经典优化方法的比较表明，残留率降低了70％以上，这导致干涉相中的变形较小。