一种抗密集欺骗式干扰的机载雷达动目标检测方法

密集欺骗式干扰不仅会引起大量虚警，还会抬高恒虚警检测器的门限，导致机载雷达的动目标检测性能严重下降。针对此问题，该文提出一种基于数据拟合的机载雷达抗密集欺骗式干扰的动目标检测算法。该算法选取待检测单元附近的数据样本构造基矩阵，对待处理数据进行最小二乘拟合；同时，对拟合系数的边界进行自适应约束以保护可能存在的目标信号。该算法可以有效滤除密集欺骗式干扰，消除其带来的虚警，能够显著改善机载雷达的动目标检测性能。基于实测数据的实验结果验证了该算法的有效性。

A Moving Target Detection Method to Suppress Dense Deception Jamming for Airborne Radar

The presence of dense deception jamming not only causes numerous false alarms but also raises the threshold of constant false alarm rate detector, which severely degrades the detection performance of airborne radar. To suppress the dense deception jamming, a moving target detection method based on data fitting is proposed. Firstly, a data basis matrix is constructed utilizing sample data adjacent to the cell under test, which is used to represent the test data in the form of least-square fitting. Simultaneously, an upper-bound constraint is adaptively calculated to protect target signals from being fitted. The proposed method can effectively suppress the dense deception jamming and significantly improve the moving target detection performance of airborne radar. The effectiveness of the proposed method is verified by the experimental results on measured radar data.