一种求解分布式目标通道最优极化的快速算法

针对现有分布式目标通道最优极化算法存在运算量偏大等问题,以算法的实用性为目的,在理论分析的基础上提出一种求解分布式目标通道最优极化的快速算法.首先将任意通道下的天线接收功率模型统一为同极化通道下的天线接收功率拓展模型,然后对该拓展模型进行变换极化基处理,在此基础上理论确定目标最优极化在(r,θ)平面上的位置区间,从而为简化目标最优极化求解或预判目标最优极化位置等提供理论支撑.为获取目标最优极化,采用区间二分法在目标最优极化位置区间内迭代搜索.通过对比实验对算法运算速度和实现方面予以验证.

Abstract：

Aiming at the large mount of calculation of the traditional algorithms for polarimetric power optimization of random target in arbitrary channel, a fast algorithm is proposed in this article. Firstly, the function of received power in arbitrary channel is unified as the form of copolar power. Then based on the change of polarimetric basis,the copotar power is analyzed theoretically to obtain the minimum interval of target optimal polarization state in (r,θ)plane, which provides theoretic support for simplifying the process of obtaining optimal polarization states or anticipating their positions. In order to obtain optimal polarization states, the interval dichotomy is used to search in the minimum interval of target optimal polarization state, The experiment results have demonstrated that the proposed algorithm has better performance than the Lagrange multiplier method or the method of traversal search in algorithmic realization and computational speed.     

一种基于区域生长原理的油库目标聚类定位方法

利用油罐目标相对集中而虚假目标相对较离散的分布特点,提出了一种基于区域生长原理的聚类方法.对于实际的遥感光学图像,所提方法既能将油罐目标聚类定位油库区域,又能自动去除虚假油罐目标.实验表明,该方法在油库检测定位上准确率高,是一种实用有效、运算量小的聚类方法.     

合成孔径雷达对地观测应用中目标感兴趣区域的自动获取

在简要评述国内外对地观测应用中,利用SAR图像进行目标ROI的自动获取方面的研究成果及存在问题的基础上,提出了一种SAR图像目标ROI自动获取新方案,包括SAR图像自动目标检测方案和SAR图像自动目标鉴别方案并解决其中的关键技术。实测数据的实验结果证明了新方案具有稳健性强、适用性广、自动化程度高、计算量小、工程实现易等特点,说明了该方案对于空间对地观测具有广泛的应用前景。