Hu Cheng, Liu Changjiang, Zeng Tao. Bistatic Forward Scattering Radar Detection and Imaging[J]. Journal of Radars, 2016, 5(3): 229-243. doi: 10.12000/JR16058
Citation: Wang Wen-qin, Cheng Sheng-juan, Shao Huai-zong. MIMO-OFDM Chirp Waveform Diversity Design and Implementation Based on Sparse Matrix and Correlation Optimization[J]. Journal of Radars, 2015, 4(1): 1-10. doi: 10.12000/JR14148

MIMO-OFDM Chirp Waveform Diversity Design and Implementation Based on Sparse Matrix and Correlation Optimization

DOI: 10.12000/JR14148
  • Received Date: 2014-12-04
  • Rev Recd Date: 2015-02-04
  • Publish Date: 2015-02-28
  • The waveforms used in Multiple-Input Multiple-Output (MIMO) Synthetic Aperture Radar (SAR) should have a large time-bandwidth product and good ambiguity function performance. A scheme to design multiple orthogonal MIMO SAR Orthogonal Frequency Division Multiplexing (OFDM) chirp waveforms by combinational sparse matrix and correlation optimization is proposed. First, the problem of MIMO SAR waveform design amounts to the associated design of hopping frequency and amplitudes. Then a iterative exhaustive search algorithm is adopted to optimally design the code matrix with the constraints minimizing the block correlation coefficient of sparse matrix and the sum of cross-correlation peaks. And the amplitudes matrix are adaptively designed by minimizing the cross-correlation peaks with the genetic algorithm. Additionally, the impacts of waveform number, hopping frequency interval and selectable frequency index are also analyzed. The simulation results verify the proposed scheme can design multiple orthogonal large time-bandwidth product OFDM chirp waveforms with low cross-correlation peak and sidelobes and it improves ambiguity performance.

     

  • [1]
    Wang W Q. Multi-Antenna Synthetic Aperture Radar[M]. New York: CRC Press, 2013: 1-13.
    [2]
    周伟, 刘永祥,黎湘, 等. MIMO-SAR 技术发展概况及应用浅 析[J]. 雷达学报, 2014, 3(1): 10-18. Zhou Wei, Liu Yong-xiang, Li Xiang, et al.. The overview of the development and application of MIMO-SAR technology[J]. Journal of Radars, 2014, 3(1): 10-18.
    [3]
    Wang W Q. MIMO SAR imaging: potential and challenges[J]. IEEE Aerospace and Electronic Systems Magazine, 2013, 27(8): 18-23.
    [4]
    武其松, 井伟, 刑孟道, 等. MIMO SAR 大测绘带成像[J]. 电 子与信息学报, 2009, 31(4): 772-775. Wu Qi-song, Jing Wei, Xing Meng-dao, et al.. The large swath imaging of MIMO SAR[J]. Journal of Electronics Information Technology, 2009, 31(4): 772-775.
    [5]
    王力宝. 多输入多输出合成孔径雷达关键技术研究[D]. [博士 论文], 国防科学技术大学, 2010. Wang Li-bao. Key technology research of multiple input multiple output Synthetic Aperture Radar[D]. [Ph.D. dissertation], National University of Defense Technology, 2010.
    [6]
    Tang B, Tang J, Peng Y N, et al.. Waveform optimization for MIMO radar in colored noise: further results for estimationoriented criteria[J]. IEEE Transactions on Signal Processing, 2012, 60(3): 1517-1522.
    [7]
    Krieger G. MIMO-SAR: opportunities and pitfalls[J]. IEEE Transactions on Geoscience and Remote Sensing, 2014, 52(5): 2628-2645.
    [8]
    Cerutti-Maori D, Sikaneta I, and Klare J. MIMO SAR processing for multichannel high-resolution wide-swath radars[J]. IEEE Transactions on Geoscience and Remote Sensing, 2014, 52(8): 5034-5055.
    [9]
    Meng C Z, Xu J, Xia X G, et al.. MIMO-SAR waveform separation based on inter-pulse phase modulation and rangedoppler decouple filtering[J]. Electronics Letters, 2013, 49(6): 420-422.
    [10]
    姚建国. Costas 序列在雷达信号设计中的应用研究[J]. 电子工 程师, 2007, 33(5): 1-6. Yao Jian-guo. Application of Costas sequences in radar signal design[J]. Electronic Engineer, 2007, 33(5): 1-6.
    [11]
    Deng H. Synthesis of binary sequences with good autocorrelation and cross-correlation properties by simulated annealing[J]. IEEE Transactions on Aerospace and Electronic Systems, 1996, 32(1): 98-107.
    [12]
    Deng H. Polyphase code design for orthogonal netted radar systems[J]. IEEE Transactions on Signal Processing, 2004, 52(1): 3126-3135.
    [13]
    Deng H. Discrete frequency-coding waveform design for netted radar systems[J]. IEEE Signal Processing Letters, 2004, 11(2): 179-182.
    [14]
    黄琼丹, 李勇, 付银娟. 多载频类随机相位编码雷达信号设计 与特性分析[J]. 西北工业大学学报, 2013, 31(6): 947-951. Huang Qiong-dan, Li Yong, and Fu Yin-juan.. Design and characterization of multi-carrier type random phase encoding radar signal[J]. Journal of Northwestern Polytechnical University, 2013, 31(6): 947-951.
    [15]
    邓斌, 魏玺章, 黎湘. 基于编码序列随机移位的MCPC 雷达 信号设计方法研究[J]. 国防科技大学学报, 2011, 33(2): 68-72. Deng Bin, Wei Xi-zhang, and Li Xiang. MCPC radar signal design method based on coding sequence of random shift[J]. Journal of National University of Defense Technology, 2011, 33(2): 68-72.
    [16]
    张劲东, 王海青, 朱晓华. 基于高分辨率距离像的UWB 雷达 信号设计[J]. 科学导报, 2008, 26(20): 69-71. Zhang Jin-dong, Wang Hai-qing, and Zhu Xiao-hua. UWB radar signal design based on high resolution range[J]. Science Guide, 2008, 26(20): 69-71.
    [17]
    Khan H A and Edwards D J. Doppler problems in orthogonal MIMO radars[C]. Proceedings of IEEE International Radar Conference, Verona, NY, USA, 2006: 24-27.
    [18]
    Stoica P, Li J, Xie Y, et al.. On probing signal design for MIMO radar[J]. IEEE Transactions on Signal Processing, 2007, 55(8): 4151-4161.
    [19]
    Yang Y and Blum R S. MIMO radar waveform design based on multual information and minimum mean-square error estimation[J]. IEEE Transactions on Aerospace and Electronic Systems, 2007, 43(1): 330-343.
    [20]
    Yang Y and Blum R S. Minimax robust MIMO radar waveform design[J]. IEEE Journal of Selected Topics in Signal Processing, 2007, 1(1): 147-155.
    [21]
    Yang Y, Blum R S, He Z S, et al.. MIMO radar waveform design via alternating projection[J]. IEEE Transactions on Signal Processing, 2010, 58(3): 1440-1445.
    [22]
    Leshem A, Naparstek O, Nehorai A, et al.. Information theoretic adaptive radar waveform design for multiple extended targets[J]. IEEE Journal of Selected Topics in Signal Processing, 2007, 1(1): 42-55.
    [23]
    Li J, Stoica P, Zheng X, et al.. Signal synthesis and receiver design for MIMO radar imaging[J]. IEEE Transactions on Signal Processing, 2008, 56(8): 3959-3968.
    [24]
    Li J, Xu L Z, Stoica P, et al.. Range compression and waveform optimization for MIMO radar: a cramer-rao bound based study[J]. IEEE Transactions on Signal Processing, 2008, 56(1): 218-232.
    [25]
    Mittermayer J and Martinez J M. Analysis of range ambiguity suppression in SAR by up and down chirp modulation for point and distributed targets[C]. Proceedings of IEEE Geoscience and Remote Sensing Symposium, 2003: 4077-4079.
    [26]
    Wang W Q. MIMO SAR chirp modulation diversity waveform design[J]. IEEE Geoscience and Remote Sensing Letters, 2014, 11(9): 1644-1648.
    [27]
    Levanon N and Mozeson E. Radar Signals[M]. John Wiley Sons, Inc, 2004: 235-256.
    [28]
    Wang W Q. Mitigating range ambiguities in high PRF SAR with OFDM waveform diversity[J]. IEEE Geoscience and Remote Sensing Letters, 2013, 10(1): 101-105.
    [29]
    Kim J H, Younis M, Moreira A, et al.. A novel OFDM chirp waveform scheme for use of multiple transmitters in SAR[J]. IEEE Geoscience and Remote Sensing Letters, 2013, 10(3): 568-572.
    [30]
    Wang J, Liang X D, and Ding C B. An improved OFDM chirp waveform used for MIMO SAR system[J]. Science China Information Sciences, 2014, DOI: 10.1007/s11432-013-4966-7.
    [31]
    Gogineni S and Nehorai A. Frequency-hopping code design for MIMO radar estimation using sparse modeling[J]. IEEE Transactions on Signal Processing, 2012, 60(6): 3022-3035.
  • Relative Articles

    [1]LI Yi, DU Lan, ZHOU Ke’er, DU Yuang. Deep Network for SAR Target Recognition Based on Attribute Scattering Center Convolutional Kernel Modulation[J]. Journal of Radars, 2024, 13(2): 443-456. doi: 10.12000/JR24001
    [2]LI Zhongyu, GUI Liang, HAI Yu, WU Junjie, WANG Dangwei, WANG Anle, YANG Jianyu. Ultrahigh-resolution ISAR Micro-Doppler Suppression Methodology Based on Variational Mode Decomposition and Mode Optimization[J]. Journal of Radars, 2024, 13(4): 852-865. doi: 10.12000/JR24043
    [3]WANG Xiang, WANG Yumiao, CHEN Xingyu, ZANG Chuanfei, CUI Guolong. Deep Learning-based Marine Target Detection Method with Multiple Feature Fusion[J]. Journal of Radars, 2024, 13(3): 554-564. doi: 10.12000/JR23105
    [4]DING Zihang, XIE Junwei, WANG Bo. Missing Covariance Matrix Recovery with the FDA-MIMO Radar Using Deep Learning Method[J]. Journal of Radars, 2023, 12(5): 1112-1124. doi: 10.12000/JR23002
    [5]DONG Yunlong, ZHANG Zhaoxiang, DING Hao, HUANG Yong, LIU Ningbo. Target Detection in Sea Clutter Using a Three-feature Prediction-based Method[J]. Journal of Radars, 2023, 12(4): 762-775. doi: 10.12000/JR23037
    [6]GONG Zhihua, LI Kaiming, DUAN Pengwei, CHEN Chunjiang. Attitude and Orbital Coupled Modeling and Micro-Doppler Characteristics Analysis of the Projectile with Initial Disturbances[J]. Journal of Radars, 2023, 12(4): 793-803. doi: 10.12000/JR23026
    [7]TIAN Ye, DING Chibiao, ZHANG Fubo, SHI Min’an. SAR Building Area Layover Detection Based on Deep Learning[J]. Journal of Radars, 2023, 12(2): 441-455. doi: 10.12000/JR23033
    [8]HE Mi, PING Qinwen, DAI Ran. Fall Detection Based on Deep Learning Fusing Ultrawideband Radar Spectrograms[J]. Journal of Radars, 2023, 12(2): 343-355. doi: 10.12000/JR22169
    [9]ZHANG Yushi, LI Xiaoyu, ZHANG Jinpeng, XIA Xiaoyun. Sea Clutter Spectral Parameters Prediction and Influence Factor Analysis Based on Deep Learning[J]. Journal of Radars, 2023, 12(1): 110-119. doi: 10.12000/JR22133
    [10]DUAN Keqing, LI Xiang, XING Kun, WANG Yongliang. Clutter Mitigation in Space-based Early Warning Radar Using a Convolutional Neural Network[J]. Journal of Radars, 2022, 11(3): 386-398. doi: 10.12000/JR21161
    [11]CHEN Xiaolong, CHEN Weishi, RAO Yunhua, HUANG Yong, GUAN Jian, DONG Yunlong. Progress and Prospects of Radar Target Detection and Recognition Technology for Flying Birds and Unmanned Aerial Vehicles (in English)[J]. Journal of Radars, 2020, 9(5): 803-827. doi: 10.12000/JR20068
    [12]XU Shuwen, BAI Xiaohui, GUO Zixun, SHUI Penglang. Status and Prospects of Feature-based Detection Methods for Floating Targets on the Sea Surface (in English)[J]. Journal of Radars, 2020, 9(4): 684-714. doi: 10.12000/JR20084
    [13]CHEN Huiyuan, LIU Zeyu, GUO Weiwei, ZHANG Zenghui, YU Wenxian. Fast Detection of Ship Targets for Large-scale Remote Sensing Image Based on a Cascade Convolutional Neural Network[J]. Journal of Radars, 2019, 8(3): 413-424. doi: 10.12000/JR19041
    [14]DING Hao, LIU Ningbo, DONG Yunlong, CHEN Xiaolong, GUAN Jian. Overview and Prospects of Radar Sea Clutter Measurement Experiments[J]. Journal of Radars, 2019, 8(3): 281-302. doi: 10.12000/JR19006
    [15]Wang Jun, Zheng Tong, Lei Peng, Wei Shaoming. Study on Deep Learning in Radar[J]. Journal of Radars, 2018, 7(4): 395-411. doi: 10.12000/JR18040
    [16]Xu Feng, Wang Haipeng, Jin Yaqiu. Deep Learning as Applied in SAR Target Recognition and Terrain Classification[J]. Journal of Radars, 2017, 6(2): 136-148. doi: 10.12000/JR16130
    [17]Wang Siyu, Gao Xin, Sun Hao, Zheng Xinwei, Sun Xian. An Aircraft Detection Method Based on Convolutional Neural Networks in High-Resolution SAR Images[J]. Journal of Radars, 2017, 6(2): 195-203. doi: 10.12000/JR17009
    [18]Chen Xiaolong, Guan Jian, He You, Yu Xiaohan. High-resolution Sparse Representation and Its Applications in Radar Moving Target Detection[J]. Journal of Radars, 2017, 6(3): 239-251. doi: 10.12000/JR16110
    [19]Chen Xiao-long, Dong Yun-long, Li Xiu-you, Guan Jian. Modeling of Micromotion and Analysis of Properties of Rigid Marine Targets[J]. Journal of Radars, 2015, 4(6): 630-638. doi: 10.12000/JR15079
    [20]Chen Xiao-lng, Guan jian, He You. Applications and Prospect of Micro-motion Theory in the Detection of Sea Surface Target[J]. Journal of Radars, 2013, 2(1): 123-134. doi: 10.3724/SP.J.1300.2012.20102
  • Cited by

    Periodical cited type(1)

    1. 陈园园,张晓丽,高显连,高金萍. 基于Sentinel-1和Sentinel-2A的西小山林场平均树高估测. 应用生态学报. 2021(08): 2839-2846 .

    Other cited types(4)

  • 加载中

Catalog

    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索
    Article views(3822) PDF downloads(1733) Cited by(5)
    Proportional views
    Related

    /

    DownLoad:  Full-Size Img  PowerPoint