计算机科学 ›› 2013, Vol. 40 ›› Issue (1): 294-297.

• 图形图像与模式识别 • 上一篇    下一篇

基于稀疏表示和时频变换的ISAR成像算法

王保平,孙超,郭俊杰   

  1. (西北工业大学无人机特种技术重点实验室 西安710065)
  • 出版日期:2018-11-16 发布日期:2018-11-16

ISAR Imaging Algorithm Based on Sparse Representation and Time-frequency Transform

  • Online:2018-11-16 Published:2018-11-16

摘要: 逆合成孔径雷达对空中机动飞行目标进行成像,在成像积累时间内,成像投影平面和横向尺度随时间变化, 许多参数很难准确提取,人们无法获得更多的先验知识。一般采用鲁棒性强的距离一多普勒(Rv)算法进行成像,但传 统的RI)成像算法基于目标匀速转动和方位均匀采样的假设,若用其对机动目标进行成像,则图像模糊,尤其对于随 机缺损的雷达回波数据,其成像质量显著下降,甚至无法辫识。通过引入稀疏表示和时频变换,提出了一种基于稀疏 表示和时频变换的距离一瞬时多普勒成像算法,其可对一般机动飞行目标进行有效成像。实验结果验证了所提算法的 有效性和可行性。

关键词: 逆合成孔径雷达,稀疏表示,时频变换,时频基

Abstract: Inverse synthetic aperture radar images maneuvering targets, and during the coherent processing interval time, imaging projection plane and the scale of cross-range change with time, so many parameters are difficult to accu- rately extract and more prior knowledge can't be acquired. In general, the robust rangcdoppler (RD) imaging algorithm is used. But the conventional RI)imaging algorithm is based on the hypothesis of the target rotating uniformly and sam- pling uniformity in azimuth. For maneuvering target imaging, RD algorithm will make the image fuzzy. Especially for ra- dar gapped data, the performance of imaging descends greatly and even cant be identified. This paper introduced a range instantaneous Doppler imaging algorithm based on sparse representation and time-frectuency transform which can effec- tively image the maneuvering target. hhe experimental results validate the effectiveness and feasibility of this approach.

Key words: Inverse synthetic aperture radar, Sparse representation, Timcfrcqucncy transform, Timcfrcqucncy basis

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