| 引用本文: | 钱卫平,余汉晨,张艳.协方差压缩感知逆合成孔径雷达成像技术.[J].国防科技大学学报,2018,40(3):95-100.[点击复制] |
| QIAN Weiping,YU Hanchen,ZHANG Yan.Inverse synthetic aperture radar imaging via covariance compressive sensing[J].Journal of National University of Defense Technology,2018,40(3):95-100[点击复制] |
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| 协方差压缩感知逆合成孔径雷达成像技术 |
| 钱卫平1, 余汉晨1,2, 张艳1,2 |
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(1. 空间目标测量重点实验室， 北京 100094;2. 北京跟踪与通信技术研究所， 北京 100094)
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| 摘要: |
| 为解决低信噪比条件下短观测时间雷达成像问题，提出一种基于回波协方差矩阵处理的压缩感知逆合成孔径雷达成像技术。该方法构建了回波协方差矩阵层面下的压缩感知问题模型，并通过特定的线性变换降低环境噪声对成像结果的影响。在仿真实验中，通过处理短观测时间和低信噪比条件下的模拟回波数据，该方法获得比传统压缩感知方法像质更好、对比度更强的目标成像结果。同时，其成像结果的目标背景比和背景噪声能量两个雷达图像评价指标都优于传统方法，进一步验证了该方法的有效性。 |
| 关键词: 协方差压缩感知 逆合成孔径雷达 高分辨率 短观测时间 低信噪比 |
| DOI：10.11887/j.cn.201803015 |
| 投稿日期：2017-04-20 |
| 基金项目:国家863计划资助项目（2014AA8083024） |
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| Inverse synthetic aperture radar imaging via covariance compressive sensing |
| QIAN Weiping1, YU Hanchen1,2, ZHANG Yan1,2 |
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(1. Key Laboratory of Space Object Measurement, Beijing 100094, China;2.
2. Beijing Institute of Tracking and Telecommunications Technology, Beijing 100094, China)
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| Abstract: |
| In order to solve the problem of low SNR(signal to noise ratio) radar imaging under short observation time, a compressive sensing inverse synthetic aperture radar imaging technique based on echo covariance matrix processing was proposed. The method constructs the compressive sensing problem model under the echo covariance matrix, and reduces the influence of noise on the imaging results through a specific linear transformation. By processing the simulated echo data under the condition of short observation time and low SNR, the method obtained target imaging results with higher quality and higher contrast than the traditional compressive sensing method. In the simulation experiment, the target background ratio and the background noise energy of the imaging results are better than the traditional methods, which verifies the validity of the method. |
| Keywords: covariance compressive sensing inverse synthetic aperture radar high resolution short observation time low signal to noise ratio |
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