中文摘要：

属性散射中心模型是基于几何绕射（GTD）模型完善得到，其模型参数具有频率和方位依赖特性，相比点散射模型对目标特征描述更为准确。但属性散射中心模型中也引入了参数维数增加的问题，模型参数估计相对困难。针对属性散射中心模型的参数估计，该文对图像分割后获得的独立散射中心进行研究，提出一种将部分参数降耦合的参数估计算法。通过建立合理的代价函数进行参数估计。相对传统参数估计方法，该方法无需获取准确的参数的初始值，从而在复杂性和时效性上有很大的改进。最后，基于仿真数据的实验论证了该文方法的有效性。

英文摘要：

： Modified and developed from the original Geometrical Theory of Diffraction （GTD） model, attributed scattering center model takes the advantages of both frequency and angle dependent properties for the model parameters, providing much richer information of the target. However, it also brings such problem as parameter dimension increasing. Research on the independent scattering centers a novel algorithm of parameter estimation is proposed, where the linking parameter dimension could be reduced effectively and the parameters could be estimated in precision. In the scheme, the object function is constructed to seek parameters and they can be estimated by solving the optimization. In this method, precision initial values of the parameters are not required. Thus the computational complexity is reduced. Numeric simulation results confirm the validation of the proposed algorithm.