基于高阶转动补偿的群目标ISAR成像方法

    A Method for Multi-target ISAR Based on High-order Rotation Compensation

    • 摘要: 由于多个目标的存在,雷达回波间的相干性被破坏,传统的逆合成孔径雷达成像(ISAR)处理方式失效。针对编队目标群的队形和运动特点,分析了成像中的频谱混叠与分离困难的问题,基于Keystone变换和多普勒转动相位校正,提出了一种群目标逆合成孔径补偿成像方法。首先,将包含多个目标的雷达回波通过盲信号处理的方式对目标群进行整体成像,基于Keystone校正各个目标的越距离单元走动(MTRC)和径向速度的微小差异;接着通过Brent方法估算群目标中心的等效转角和各个目标的径向位置,构建多普勒相位补偿因子,补偿长时间观测下带来的多普勒混叠;最后通过DBSCAN和自聚焦完成多个目标的精细化成像。仿真实验结果表明,该方法能够得到群目标良好的聚焦图像,且能够获取目标之间的相对位置关系,自聚焦后的单目标图像能够提供更多的细节信息,验证了文中方法的正确性和有效性。

       

      Abstract: Due to the presence of multiple targets, the coherence of radar echoes is disrupted, rendering traditional inverse synthetic aperture radar (ISAR) imaging methods ineffective. This paper addresses the challenges of spectrum aliasing and separation difficulties in ISAR imaging of formation targets by analyzing their formation and motion characteristics. We propose a high-density multi-target ISAR imaging method based on Keystone transform and high-order rotation phase compensation. First, the echoes of multiple targets are processed via blind signal separation to generate an initial composite image of the target group. The Keystone transform is applied to migration through resolution cell (MTRC) and minor radial velocity variations among individual targets. Next, the equivalent rotation angle and radial position of the target group′s center are estimated using Brent method, and a high-order Doppler phase factor is constructed to compensate for Doppler aliasing caused by long observation times. Finally, fine-resolution imaging of each target is achieved through DBSCAN clustering. Simulation results demonstrate that the proposed method enables well-focused imaging of group targets while accurately resolving their relative spatial relationships. Furthermore, auto-focused single-target images deliver significantly finer details, thereby validating the correctness and effectiveness of the proposed approach.

       

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