基于参数化稀疏表征高速目标ISAR成像方法

ISAR imaging method for high speed moving target based on parametric sparse representation

针对高速运动目标逆合成孔径雷达(ISAR)成像问题,提出一种基于参数化稀疏表征的高速目标ISAR成像方法.首先,对高速运动目标回波信号特点进行分析,构造包含目标未知速度的参数化感知矩阵,建立回波信号稀疏模型.其次,采用自适应寻优算法,同时获得优化的感知矩阵及目标运动速度,基于压缩感知理论,在稀疏采样条件下重构目标ISAR像.相较于已有方法,所提方法可避免ISAR成像中复杂的运动补偿处理,并具有较低的运算复杂度和较好的鲁棒性.仿真实验验证了理论分析与所提成像方法的正确性和有效性.

To obtain the inverse synthetic aperture radar（ISAR）image of high speed moving target,an ISAR imaging method for high speed moving target was proposed based on the parametric sparse representation.Firstly,the echo signal of high speed moving target was analyzed and sparse was represented via designing aparametric sensing matrix containing the target unknown velocity.Subsequently,through the adaptive optimization algorithm,both the optimal sensing matrix and the estimated target velocity can be obtained.On the basis of the compressed sensing theory,the target ISAR image can be reconstructed with sparse sampling data.Compared to the existing method,the proposed method can avoid the complex motion compensation in traditional ISAR imaging.Moreover,it possesses lower computational complexity and better robustness.Finally,simulations were performed to verify the effectiveness of the proposed method.