Advanced Search
Volume 43 Issue 12
Dec.  2021
Turn off MathJax
Article Contents
Donghe LIU, Yongbo ZHAO, Xiaojiao PANG, Chenghu CAO, Sheng CHEN. DOA Estimation Algorithm Based on Reduced-dimensional Beamspace with Real-valued ESPRIT for Monostatic MIMO Radar[J]. Journal of Electronics & Information Technology, 2021, 43(12): 3639-3646. doi: 10.11999/JEIT200485
Citation: Donghe LIU, Yongbo ZHAO, Xiaojiao PANG, Chenghu CAO, Sheng CHEN. DOA Estimation Algorithm Based on Reduced-dimensional Beamspace with Real-valued ESPRIT for Monostatic MIMO Radar[J]. Journal of Electronics & Information Technology, 2021, 43(12): 3639-3646. doi: 10.11999/JEIT200485

DOA Estimation Algorithm Based on Reduced-dimensional Beamspace with Real-valued ESPRIT for Monostatic MIMO Radar

doi: 10.11999/JEIT200485
Funds:  The Fund for Foreign Scholars in University Research and Teaching Programs(B18039)
  • Received Date: 2020-06-15
  • Rev Recd Date: 2021-04-02
  • Available Online: 2021-05-06
  • Publish Date: 2021-12-21
  • The Direction Of Arrival (DOA) estimation is a hot topic for a monostatic Multiple Input Multiple Output (MIMO) radar in recent years. The conventional Estimation of Signal Parameters via Rotational Invariance Technique (ESPRIT) algorithms need to pay much computation cost because of the high-dimensional MIMO radar data. When the Signal-to-Noise Ratio (SNR) is low and the number of sample are small, the performance of the conventional ESPRIT algorithms degrades seriously. To overcome the disadvantages of conventional ESPRIT algorithms, a novel algorithm which is called as reduced-dimensional beamspace with real-valued ESPRIT for monostatic MIMO radar is proposed. To eliminate the redundancy, the high-dimensional MIMO radar data is transformed into the low-dimensional data through the transformation matrix. To reduce further the computation complexity, the low-dimensional data is transformed into beamspace. Then the real-valued rotation invariance equation is constructed to estimate the target’s DOA. Simulation results show the proposed algorithm has better angle estimation performance and less computation burden than traditional ESPRIT algorithms.
  • loading
  • [1]
    HAIMOVICH A M, BLUM R S, and CIMINI L J. MIMO Radar with Widely Separated antennas[J]. IEEE Signal Processing Magazine, 2008, 25(1): 116–129. doi: 10.1109/MSP.2008.4408448
    [2]
    LI Jian and STOICA P. MIMO radar with colocated antennas[J]. IEEE Signal Processing Magazine, 2007, 24(5): 106–114. doi: 10.1109/MSP.2007.904812
    [3]
    ZHAO Yongbo, SHUI Penglang, and LIU Hongwei. Computationally efficient DOA estimation for MIMO radar[C]. The 2nd International Congress on Image and Signal Processing, Tianjin, China, 2009: 1–3. doi: 10.1109/CISP.2009.5304414.
    [4]
    ZHANG X, HUANG Y, CHEN C, et al. Reduced-complexity Capon for direction of arrival estimation in a monostatic multiple-input multiple-output radar[J]. IET Radar, Sonar & Navigation, 2012, 6(8): 796–801. doi: 10.1049/iet-rsn.2011.0343
    [5]
    JINLI C, HONG G, and WEIMIN S. Angle estimation using ESPRIT without pairing in MIMO radar[J]. Electronics Letters, 2008, 44(24): 1422–1423. doi: 10.1049/el:20089089
    [6]
    ZHANG X and XU D. Low-complexity ESPRIT-based DOA estimation for colocated MIMO radar using reduced-dimension transformation[J]. Electronics Letters, 2011, 47(4): 283–284. doi: 10.1049/el.2010.3279
    [7]
    文才, 王彤. 单基地MIMO雷达降维酉ESPRIT算法[J]. 系统工程与电子技术, 2014, 36(6): 1062–1067. doi: 10.3969/j.issn.1001-506X.2014.06.08

    WEN Cai and WANG Tong. Reduced-dimensional unitary ESPRIT algorithm for monostatic MIMO radar[J]. Systems Engineering and Electronics, 2014, 36(6): 1062–1067. doi: 10.3969/j.issn.1001-506X.2014.06.08
    [8]
    ZHANG Yu, ZHANG Gong, and WANG Xinhai. Computationally efficient DOA estimation for monostatic MIMO radar based on covariance matrix reconstruction[J]. Electronics Letters, 2017, 53(2): 111–113. doi: 10.1049/el.2016.3818
    [9]
    徐保庆, 赵永波, 庞晓娇. 基于实值处理的联合波束域双基地MIMO雷达测角算法[J]. 电子与信息学报, 2019, 41(7): 1721–1727. doi: 10.11999/JEIT180766

    XU Baoqing, ZHAO Yongbo, and PANG Xiaojiao. Joint real-valued beamspace-based method for angle estimation in bistatic MIMO radar[J]. Journal of Electronics &Information Technology, 2019, 41(7): 1721–1727. doi: 10.11999/JEIT180766
    [10]
    LI Jianfeng, HE Yi, HE Lang, et al. DOD and DOA estimation for MIMO radar based on combined MUSIC and sparse Bayesian learning[C]. 2019 International Applied Computational Electromagnetics Society Symposium - China (ACES), Nanjing, China, 2019: 1–2. doi: 10.23919/ACES48530.2019.9060555.
    [11]
    YANG Zai and XIE Lihua. On gridless sparse methods for multi-snapshot DOA estimation[C]. 2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Shanghai, China, 2016: 3236–3240. doi: 10.1109/ICASSP.2016.7472275.
    [12]
    YANG Zai, XIE Lihua, and ZHANG Cishen. Off-grid direction of arrival estimation using sparse bayesian inference[J]. IEEE Transactions on Signal Processing, 2013, 61(1): 38–43. doi: 10.1109/TSP.2012.2222378
    [13]
    WEN Fangqing, HUANG Dongmei, WANG Ke, et al. DOA estimation for monostatic MIMO radar using enhanced sparse Bayesian learning[J]. The Journal of Engineering, 2018, 2018(5): 268–273. doi: 10.1049/joe.2017.0872
    [14]
    MAO Chenxing and WEN Fangqing. Off-grid DOA estimation for Colocated MIMO radar via sparse Bayesian learning[C]. 2019 International Applied Computational Electromagnetics Society Symposium - China (ACES), Nanjing, China, 2019: 1–2. doi: 10.23919/ACES48530.2019.9060628.
    [15]
    LIU Tingting, WEN Fangqing, ZHANG Lei, et al. Off-grid DOA estimation for Colocated MIMO radar via reduced-complexity sparse Bayesian learning[J]. IEEE Access, 2019, 7: 99907–99916. doi: 10.1109/ACCESS.2019.2930531
    [16]
    CHEN Fangfang, ZHANG Jinghao, and DAI Jisheng. DOD and DOA estimation for bistatic MIMO radars with sparse Bayesian learning[C]. 2018 International Workshop on Antenna Technology (iWAT), Nanjing, China, 2018: 1–4. doi: 10.1109/IWAT.2018.8379194.
    [17]
    ZOLTOWSKI M D, KAUTZ G M, and SILVERSTEIN S D. Beamspace root-MUSIC[J]. IEEE Transactions on Signal Processing, 1993, 41(1): 344. doi: 10.1109/TSP.1993.193151
    [18]
    ZOLTOWSKI M D, HAARDT M, and MATHEWS C P. Closed-form 2-D angle estimation with rectangular arrays in element space or beamspace via unitary ESPRIT[J]. IEEE Transactions on Signal Processing, 1996, 44(2): 316–328. doi: 10.1109/78.485927
    [19]
    FORSTER P and VEZZOSI G. Application of spheroidal sequences to array processing[C]. 1987 IEEE International Conference on Acoustics, Speech, and Signal Processing, Dallas, USA, 1987: 2268–2271. doi: 10.1109/ICASSP.1987.1169421.
  • 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

    Figures(8)

    Article Metrics

    Article views (1090) PDF downloads(129) Cited by()
    Proportional views
    Related

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return