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.

A Fast Algorithm for Polarimetric Power Optimization of Random Target

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.