基于方位特性表征的属性散射中心模型参数估计方法

An Aspect-Dependence Characteristics-Based Approach for Parameter Estimation of Attribute Scattering Center Model

  • 摘要: 属性散射中心模型使用一组富含物理意义的特征参数描述高频区目标的散射特性,其模型参数中具有的频率和方位依赖项为目标识别提供了重要的特征信息。但复杂的模型形式使得参数的提取只能在图像域中进行,其中一个关键的步骤就是图像分割。由于属性散射中心在图像域中表现形式的复杂性,传统的分割算法往往不能准确地描述划分区域中散射的内在本质,使得参数的估计误差偏大。针对此缺陷,提出了一种基于方位特性表征的参数估计方法。该方法利用散射点的方位函数对散射类型进行判断,指导散射中心区域的划分以提高参数的估计精度。仿真实验验证了方法的有效性。

     

    Abstract: Attribute scattering center model provides a richer physical description of target scattering at high frequencies. The frequency and aspect dependence in the model is an important feature for target recognition. But the parameters have to be extracted in image domain because of complexity of model function, and image segmentation is a key step in the process. Due to the complexity of the representation of scattering center in image domain, the inherent scattering mechanism in the separated region can not be described accurately using traditional segmentation algorithm, which results in the failure of the model parameter estimation. Aiming at the problem, a parameter estimation method based on aspect-dependence characteristics is presented. It employs the aspect angle function to distinguish the scattering type, this can provide a useful guidance for the partition of image and extraction of feature parameters. The result of simulation has shown the feasibility of the method.

     

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