一种子视相干优化的极化SAR船只检测方法

A Polarimetric SAR Ship Detection Method Based on Sub-look Coherent Optimization

针对传统单极化SAR船只检测能力不足的问题,提出了一种基于极化SAR图像子视相干的方法来检测船只。该方法在船只和海杂波SAR子视图相干程度分析的基础上,通过调整全极化SAR图像数据的最优极化状态得到3个优化的相干参数,并由此定义了一种最优相干积参数。由于该参数可以保留相干目标(即船只)的强度和相位,因此能够极大提高目标与背景之间的对比度,从而改善后期的目标检测性能。最后,采用机载极化SAR数据来评估本文方法,其试验结果表明,该方法能充分利用目标的极化特征以及子视相干性信息,显著提高了船海对比度,实现了船只检测性能的改进。

Aimming at the shortage problem of ship detection ability with traditional single-polarimetric SAR data,this paper proposed a sub-aperture coherence method for the enhancement of ship detection using full polarimetric SAR data. Based on the SAR sub-look coherent analysis of ship and ocean clutter, three optimal non-normalized coherences can be obtained by tuning the polarization status using the full polarimetric SAR data. And then,an optimal coherence product was defined with these coherences to preserve the intensity and phase information of the coherent target and greatly improve the contrast between the target and the clutter. The airborne polarimetric SAR data was applied to evaluate the method proposed in this paper. The experimental results show that this method can make full use of the polarization characteristics of target and the coherence information, and realize the ship detection performance improvement by greatly enhancing the contrast between ships and ocean clutter.