Resolution Enhancement Method for Bistatic ISAR One-dimensional Range Profile Under Low SNR
-
摘要: 针对双基地角使双基地ISAR(B-ISAR) 1维距离成像分辨率下降的问题，该文提出基于多量测向量(MMV)模型的复数近似消息传递(MCAMP)的B-ISAR 1维距离成像分辨率增强算法。首先，建立距离联合稀疏模型。然后，通过向量化处理将联合稀疏问题转换为块稀疏复数基追踪去噪问题，利用Kronecker积提出MCAMP算法进行求解，以得到不受双基地角影响的1维距离像。最后，通过快速傅里叶变换(FFT)代替矩阵与矩阵相乘进一步减少了计算复杂度，进而提高了算法的实现效率。仿真成像结果验证了所提方法在重构精度和重构时间方面的优势。
-
关键词:
- 双基地逆合成孔径雷达 /
- 高分辨距离像 /
- 复数近似消息传递 /
- 压缩感知
Abstract: To solve the problem of declined resolution of Bistatic Inverse Synthetic Aperture Radar (B-ISAR) imaging by bistatic angle, a B-ISAR range profile resolution enhancement algorithm is put forward based on Multiple Measurement Vector (MMV) Complex Approximate Message Passing (MCAMP). The range joint sparse model is established. By utilizing vectorization operation, the joint sparse problem is converted into a block complex basis pursuit denoising problem. To achieve the range profile which is immune to bistatic angle influence, the MCAMP algorithm is proposed by using the Kronecker product. The Fast Fourier Transform (FFT) is introduced to instead of multiplication between matrix and matrix, which improves the efficiency of the proposed algorithm by reducing the computational complexity further. Simulation imaging results verify the effectiveness and efficiency of the proposed method. -
表 1 3种算法的计算复杂度对比
算法 计算复杂度 MOMP $O\left( {{L_1}\!\!^4 + N{L_1}\!\!^3 + {L_1}NQ{N_a}} \right)$ MFOCUSS $O\left( {{L_2}{N^3} + {L_2}\left( {N + {N_a}} \right)\left( {NQ + {Q^2}} \right)} \right)$ 本文算法 $O\left( {{L_3}{N_a}Q{{\log }_2}Q} \right)$ 
下载: 导出CSV
表 2 电磁计算参数设置
参数 数值 发射站与XOZ平面夹角 0° 发射站与YOZ平面夹角 105° 接收站与XOZ平面夹角 80°～85° 接收站与YOZ平面夹角 105° 扫掠频率 10～11 GHz 频率点数 300 脉冲数 256 平均双基地角 82.5° 脉冲压缩前信噪比 0 dB
下载: 导出CSV
-
赵会朋, 王俊岭, 高梅国, 等. 基于轨道误差搜索的双基地ISAR 包络对齐算法[J]. 系统工程与电子技术, 2017, 39(6): 1235–1243 doi: 10.3969/j.issn.1001-506X.2017.06.08ZHAO Huipeng, WANG Junling, GAO Meiguo, et al. Bistatic ISAR envelope alignment algorithm based on orbit error search[J]. Systems Engineering and Electronics, 2017, 39(6): 1235–1243 doi: 10.3969/j.issn.1001-506X.2017.06.08 JIANG Y, SUN S. YEO T S, et al. Bistatic ISAR distortion and defocusing analysis[J]. IEEE Transactions on Aerospace and Electronic Systems, 2016, 52(3): 1168–1182 doi: 10.1109/TAES.2016.140028 郭宝锋, 尚朝轩, 王俊岭, 等. 基于二体模型的空间目标双基地ISAR回波模拟[J]. 系统工程与电子技术, 2016, 38(8): 1771–1779 doi: 10.3969/j.issn.1001-506X.2016.08.10GUO Baofeng, SHANG Chaoxuan, WANG Junling, et al. Bistatic ISAR echo simulation of space target based on two-body model[J]. Systems Engineering and Electronics, 2016, 38(8): 1771–1779 doi: 10.3969/j.issn.1001-506X.2016.08.10 ZHANG Shunsheng, ZHANG Wei, ZONG Zhulin, et al. High-resolution bistatic ISAR imaging based on two-dimensional compressed sensing[J]. IEEE Transactions on Antennas and Propagation, 2015, 63(5): 2098–2111 doi: 10.1109/TAP.2015.2408337 ZHANG Shunsheng, SUN Sibo, ZHANG Wei, et al. High-resolution bistatic ISAR image formation for high-speed and complex-motion targets[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2017, 8(7): 3520–3531 doi: 10.1109/JSTARS.2015.2417192 SUN Sibo, YUAN Yeshu, and JIANG Yicheng. Bistatic inverse synthetic aperture radar imaging method for maneuvering targets[J]. Journal of Applied Remote Sensing, 2016, 10(4): 045016 doi: 10.1117/1.JRS.10.045016 KANG B S, BAE J H, KANG M S, et al. Bistatic-ISAR cross-range scaling[J]. IEEE Transactions on Aerospace and Electronic Systems, 2017, 53(4): 1962–1973 doi: 10.1109/TAES.2017.2677798 KANG M S, KANG B S, LEE S H, et al. Bistatic-ISAR distortion correction and range and cross-range scaling[J]. IEEE Sensors Journal, 2017, 17(16): 5068–5078 doi: 10.1109/JSEN.2017.2713804 韩宁, 尚朝轩, 何强, 等. 基于稀疏分解的双基地ISAR一维距离成像方法[J]. 信号处理, 2012, 28(1): 54–59 doi: 10.3969/j.issn.1003-0530.2012.01.008HAN Ning, SHANG Chaoxuan, HE Qiang, et al. Method for bistatic ISAR one-dimensional range profile based on sparse decomposition[J]. Signal Processing, 2012, 28(1): 54–59 doi: 10.3969/j.issn.1003-0530.2012.01.008 DONHO D L. Compressed sensing[J]. IEEE Transactions on Information Theory, 2006, 52(4): 1289–1306 doi: 10.1109/TIT.2006.871582 MALEKI A, ANITORI L, YANG Z, et al. Asymptotic analysis of complex LASSO via Complex Approximate Message Passing (CAMP)[J]. IEEE Transactions on Information Theory, 2013, 59(7): 4290–4308 doi: 10.1109/TIT.2013.2252232 朱仁飞, 罗迎, 张群, 等. 双基地ISAR成像分析[J]. 现代雷达, 2011, 33(8): 33–38 doi: 10.3969/j.issn.1004-7859.2011.08.009ZHU Renfei, LUO Ying, ZHANG Qun, et al. Analysis of bistatic inverse synthetic aperture radar imaging[J]. Modern Radar, 2011, 33(8): 33–38 doi: 10.3969/j.issn.1004-7859.2011.08.009 DONHO D L, JOHNSTONE I M, and MPNTANARI A. Accurate prediction of phase transitions in compressed sensing via a connection to minimax denoising[J]. IEEE Transactions on Information Theory, 2013, 59(6): 3396–3433 doi: 10.1109/TIT.2013.2239356 CHEN Jie and HUO Xiaoming. Theoretical results on sparse representations of multiple-measurement vectors[J]. IEEE Transaction on Signal Processing, 2006, 54(12): 4634–4643 doi: 10.1109/TSP.2006.881263 SHANE F C, BHASKAR D R, KJERSTI E, et al. Sparse solutions to linear inverse problems with multiple measurement vectors[J]. IEEE Transaction on Signal Processing, 2005, 53(7): 2477–2488 doi: 10.1109/TSP.2005.849172 -
图(6) / 表(2)
计量
- 文章访问数: 1734
- HTML全文浏览量: 463
- PDF下载量: 43
- 被引次数: 0
下载:
