面向辅助导航复杂地形下基于极化信息的景象匹配技术研究

In modern warfare, INS (inertial navigation system) / scene matching integrated navigation is one of the most important technologies to achieve the precise strike, unmanned flight and other military actions. Compared with the most widely used INS / SAR (synthetic aperture radar) integrated navigation, INS / PolSAR (Polarimetric SAR) integrated navigation can obtain higher precision and success.rate, due to containing the distinctive polarization information reflecting scattering structures of targets. However, the current PolSAR image matching methods are mostly not multi-channel joint matching, unable to take full advantage of the polarization information to improve matching results, and they also cannot solve the difficulty of the matching over areas with large terrain undulation. These methods are not effective enough to support INS / PolSAR integrated system. To solve the above problems, based on the polarization information this project focuses on the research of scene matching over complex terrains for aided navigation. Over the areas with small terrain undulation, the multi-channel joint matching method of PolSAR images based on hypercomplex numbers will be researched. Over the areas with large terrain undulation, the matching method of DEM and PolSAR images based on polarization information will be researched. Therefore, improving the matching over areas with small terrain undulation and solving the difficulty of scene matching over areas with large terrain undulation, the project can provide technical support to the implementation and application of INS / PolSAR integrated navigation.

惯性导航（INS）/景象匹配组合制导是现代战争中精确打击、无人飞行等军事行动得以实现的重要技术之一。与目前广泛应用的INS/SAR组合方式相比，INS/极化SAR组合因其含有反应目标散射结构的极化信息，能够获得更高的制导精度和成功率。然而目前的极化SAR景象匹配方法大多并非多通道联合匹配，无法充分发挥极化信息的优势提高匹配效果，且仍无法解决强地形起伏时难以匹配成功的问题，支撑INS/极化SAR组合制导尚显薄弱。针对以上问题，面向辅助导航应用，本项目重点研究不同地形起伏条件下基于极化信息的景象匹配技术。在弱地形起伏地区，研究基于超复数的极化SAR图像多通道联合匹配方法；在强地形起伏地区，使用DEM构成基准图，研究基于共同极化特征的DEM和极化SAR图像匹配方法。从而提高弱地形起伏地区的匹配效果，解决强地形起伏地区的匹配难题，为INS/极化SAR组合制导的实现和应用提供理论基础和技术支撑。

本课题针对面向INS/极化SAR组合导航应用的景象匹配问题，通过引入具有多个虚数通道的超复数，提出了极化SAR超复数化模型和基于该模型的多通道联合景象匹配方法。课题主要研究内容和创新点总结如下：.(1) 基于统计判决理论和极化SAR图像统计特性，推导和计算了图像匹配成功概率，分析了影响图像匹配成功的关键要素,为匹配算法和相似性度量的设计提供了理论基础和技术指导。.(2) 研究了极化SAR图像的超复数表示方法，构建了极化SAR相干分解和非相干分解的四元数表达模型；基于四元数的基本运算和变换规则，推导获得了四元数表示下的极化SAR相位相关系数和夹角相关系数；提出了多级匹配方案，实现根据已有单通道SAR图像匹配方法向多通道匹配的间接升维，缓解了由变量升维带来的计算量剧增问题，从而发展了一种多通道联合的景象匹配方法。.(3) 针对强地形起伏条件下由于SAR的侧视斜距成像导致较大几何失真所带来的极化SAR图像匹配难题，推导获得了强地形起伏下DEM到共极化特征的空间映射关系，提出了基于POAS的极化SAR图像与DEM匹配方法，并分析了两者的相似度逼近。.(4) 通过在多种实测极化SAR图像中设置不同的实验条件，验证了本课题提出的多项超复数算法和方案的有效性；使用实测DEM与极化SAR图像数据，验证了基于POAS的极化SAR图像与DEM匹配方法的可靠性。