论文标题
SAR图像中地面类型检测的瑞利回归模型
Rayleigh Regression Model for Ground Type Detection in SAR Imagery
论文作者
论文摘要
这封信提出了一个非负信号的回归模型。提出的回归估计了瑞利分布式信号的平均值，该结构包括一组回归器和链接函数。对于提出的模型，我们介绍：（i）〜参数估计； （ii）〜大数据记录结果； （iii）〜一种检测技术。在这封信中，我们介绍了分数向量和Fisher Information Matrix的封闭式表达式。提出的模型已提交给广泛的蒙特卡洛模拟和测量数据。蒙特卡洛模拟用于评估最大似然估计器的性能。同样，在SAR图像中，将提出模型的检测结果与高斯，γ-和Weibull回归模型进行比较。
This letter proposes a regression model for nonnegative signals. The proposed regression estimates the mean of Rayleigh distributed signals by a structure which includes a set of regressors and a link function. For the proposed model, we present: (i)~parameter estimation; (ii)~large data record results; and (iii)~a detection technique. In this letter, we present closed-form expressions for the score vector and Fisher information matrix. The proposed model is submitted to extensive Monte Carlo simulations and to measured data. The Monte Carlo simulations are used to evaluate the performance of maximum likelihood estimators. Also, an application is performed comparing the detection results of the proposed model with Gaussian-, Gamma-, and Weibull-based regression models in SAR images.
