基于改进高斯核函数的雷达高分辨距离像目标识别算法研究

Target Recognition Algorithm of Radar High Resolution Range Profile Based on Improved Gaussian Kernel Function

针对支持向量机的核函数选择问题,在保形变换方法的基础上,分析了确定数据分布特征的重要性,给出了判断数据呈高斯分布的方法。利用支持向量机的高斯核函数,提出一种基于改进的高斯核函数雷达目标高分辨距离像的研究方法。该方法对SVM的高斯核函数进行改进,并进行核函数选择。通过改进的高斯核函数与多项式核函数进行比较,在Matlab环境下采用两种方法对高分辨距离像进行仿真,仿真方法验证并改进了高斯核函数的有效性。

Aiming at kernel function selection of support vector machine（SVM） ,the method to determine Gaussian distribution of the data is introduced by analyzing feature of data distribution based on the proposed conformal transformation method.A target recognition algorithm of radar high resolution range profile based on improved Gaussian kernel function is proposed by using Gaussian kernel function of support vector machine.The method improved SVM Gaussian kernel function and carried out the kernel function selection.Through comparing the improved Gaussian kernel function with the polynomial kernel functions,two methods are used to simulate high resolution range profile in the Matlab environment,the simulation method validate the effectiveness of Gaussian kernel function.