ISAR机动目标联合高分辨成像和参数估计

High-resolution Inverse Synthetic Aperture Radar Imaging of Maneuvering Targets Joint with Parameter Estimation

  • 摘要: 在逆合成孔径雷达(inverse synthetic aperture radar, ISAR)成像中,目标的机动特性会引入高阶相位调制,从而增加在低信噪比下成像聚焦和定标的难度。为了解决此问题,本文提出了一种联合成像和目标参数估计的算法,能够实现良好的聚焦成像和精确的图像定标处理。考虑目标转动加加速度,建立高机动性目标信号模型。针对目标转动参数和转动中心位置未知,利用最小熵方法进行联合目标成像和转动参数估计。同时,利用估计转动参数实现图像方位定标,以提取目标二维几何特征。相比传统成像算法(如时频类方法),本文方法能够获得全孔径成像分辨率,并且在低信噪比下取得较好的成像质量。最后,通过实验分析验证了本文算法的有效性。

     

    Abstract: For inverse synthetic aperture radar (ISAR) imaging, the high maneuverability of target will introduce additional Doppler modulation, which increases the difficulty of imaging and scaling in low signal-to-noise ratio (SNR). To resolve this, this paper proposes a novel algorithm of joint high-resolution imaging and parameter estimation, which can realize well-focused imaging and accurate image scaling. The signal model of target maneuverability is constructed by considering the rotational jerk. To deal with the unknown rotational rate and rotational center, the approach using minimum entropy is presented to realize these parameter estimation. Meanwhile, the estimate the rotational parameters are used for azimuth scaling by extracting the 2-D target geometry. In comparison with the conventional imaging algorithms, such as time-frequency approach, the proposed algorithm in this paper can achieve higher resolution with full aperture data, and can realize acceptable imaging performance even in low SNR. Finally, the experimental analysis is performed to confirm the effectiveness of the proposed algorithm.

     

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