A model - based polarimetric adaptive CFAR detection algorithm is derived that has a lower estimation loss. A theoretical expression is derived for constant false alarm rate of the proposed algorithm.
提出了一种基于杂波模型的极化自适应恒虚警检测算法，该算法比极化自适应匹配滤波器算法有更小的估计损失，并推导出了虚警概率表达式。
The results indicate that this technique can improve the performance of CA and OS CFAR detection in multi target interference environments without any performance loss in homogeneous environments.
结果表明，该方法在不降低均匀环境下检测性能的条件下，可以明显改善CA和OS-CFAR在多目标干扰环境下的检测性能。
The results indicate that this technique can improve the performance of CA and OS CFAR detection in multi target interference environments without any performance loss in homogeneous environments.
结果表明，该方法在不降低均匀环境下检测性能的条件下，可以明显改善CA和OS-CFAR在多目标干扰环境下的检测性能。
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