Li Bingchen, Mo Di, Song Ziqi, Wang Ning, Wang Ran, Lin Miao, Li Shiqiang
Appl Opt. 2020 Oct 10;59(29):9098-9103. doi: 10.1364/AO.401887.
In space defense, utilizing the micromotion features to distinguish real targets from interfering targets and decoys is effective. Due to the imaging of the high-speed precession target by microwave radar consisting of isolated scattering centers, there are many difficulties in using inverse synthetic aperture radar (ISAR) images for feature extraction. On the other hand, the inverse synthetic aperture ladar (ISAL) image is relatively continuous because of the short wavelength of laser, and the image sequence contains information about the variation in image length and Doppler width caused by target precession, which can be used for inverse motion parameters. By establishing an observation model of the precession target and performing image processing on the obtained ISAL image at different times, the image length sequence and Doppler width sequence can be obtained. Using the ellipse fitting method to process the obtained sequence, the precession parameters of the target can be obtained. The algorithm does not require prior information such as the radius and speed of the target motion, effectively improving the practicability of the algorithm. Finally, the effectiveness of the algorithm is verified by experimental results, and the error is controlled within 2%.
在空间防御中，利用微动特征来区分真实目标与干扰目标及诱饵是有效的。由于由孤立散射中心组成的微波雷达对高速进动目标成像，利用逆合成孔径雷达（ISAR）图像进行特征提取存在诸多困难。另一方面，逆合成孔径激光雷达（ISAL）图像因激光波长短而相对连续，且图像序列包含由目标进动引起的图像长度和多普勒宽度变化的信息，可用于反演运动参数。通过建立进动目标的观测模型并对不同时刻获取的ISAL图像进行图像处理，可得到图像长度序列和多普勒宽度序列。利用椭圆拟合方法对所得序列进行处理，可得到目标的进动参数。该算法不需要目标运动半径和速度等先验信息，有效提高了算法的实用性。最后，通过实验结果验证了算法的有效性，误差控制在2%以内。
