Volume 7 Issue 4
Aug.  2018
Turn off MathJax
Article Contents
Chen Fangxiang, Yi Wei, Zhou Tao, Kong Lingjiang. Passive Direct Location Determination for Multiple Sources Based on FRFT[J]. Journal of Radars, 2018, 7(4): 523-530. doi: 10.12000/JR18027
Citation: Chen Fangxiang, Yi Wei, Zhou Tao, Kong Lingjiang. Passive Direct Location Determination for Multiple Sources Based on FRFT[J]. Journal of Radars, 2018, 7(4): 523-530. doi: 10.12000/JR18027

Passive Direct Location Determination for Multiple Sources Based on FRFT

DOI: 10.12000/JR18027
Funds:  The National Natural Science Foundation of China (61771110), The Chang Jiang Scholars Program, The 111 Project (B17008), The Fundamental Research Funds of Central Universities (ZYGX2016J031), The Chinese Postdoctoral Science Foundation (2014M550465), Special Grant (2016T90845)
  • Received Date: 2018-03-27
  • Rev Recd Date: 2018-06-22
  • Publish Date: 2018-08-28
  • The Direct Position Determination (DPD) method can fully use the information of an observed signal, and it is known to outperform the traditional two-step methods at a low Signal-to-Noise Ratio (SNR). To solve the problem of localizing multiple transmitters with unknown Linear Frequency Modulation (LFM) signals in multi-static passive radar systems, a multi-target positioning algorithm based on DPD algorithm and FRactional Fourier Transform (FRFT) is proposed. First, according to the established signal model, the theoretically optimal high-dimensional maximum likelihood estimator is deduced; Then, to address the high computational complexity of the estimator in jointly estimating high-dimensional signal parameters and positions of sources, we propose a dimensionality reduction strategy based on the FRFT and some basic classification algorithms to transform the multi-target localizing problem to a multiple single-target localizing problem. Through this method, the position and the corresponding signal parameters of each source can be efficiently estimated by a four-dimensional grid search. Simulation results show that the proposed method outperforms the existing DPD algorithm, and it can determine the positions of sources without directly utilizing the transmitted signal information.

     

  • loading
  • [1]
    Amar A and Weiss A J. Localization of narrowband radio emitters based on Doppler frequency shifts[J]. IEEE Transactions on Signal Processing, 2008, 56(11): 5500–5508. DOI: 10.1109/TSP.2008.929655
    [2]
    贾兴江. 运动多站无源定位关键技术研究[D]. [博士论文], 国防科学技术大学, 2011: 3–42

    Jia Xing-jiang. Research on passive location technologies of multiple moving observers[D]. [Ph.D. dissertation], National University of Defense Technology, 2011: 3–42
    [3]
    Tirer T and Weiss A J. High resolution localization of narrowband radio emitters based on Doppler frequency shifts[J]. Signal Processing, 2017, 141: 288–298. DOI: 10.1016/j.sigpro.2017.06.019
    [4]
    赵勇胜, 赵拥军, 赵闯. 联合角度和时差的单站无源相干定位加权最小二乘算法[J]. 雷达学报, 2016, 5(3): 302–311. DOI: 10.12000/JR15133

    Zhao Yong-sheng, Zhao Yong-jun, and Zhao Chuang. Weighted least squares algorithm for single-observer passive coherent location using DOA and TDOA measurements[J]. Journal of Radars, 2016, 5(3): 302–311. DOI: 10.12000/JR15133
    [5]
    Weiss A J. Direct position determination of narrowband radio frequency transmitters[J]. IEEE Signal Processing Letters, 2004, 11(5): 513–516. DOI: 10.1109/LSP.2004.826501
    [6]
    Yi W, Chen Z H, Hoseinnezhad R, et al. Joint estimation of location and signal parameters for an LFM emitter[J]. Signal Processing, 2017, 134: 100–112. DOI: 10.1016/j.sigpro.2016.11.014
    [7]
    Oispuu M and Nickel U. Direct detection and position determination of multiple sources with intermittent emission[J]. Signal Processing, 2010, 90(12): 3056–3064. DOI: 10.1016/j.sigpro.2010.05.010
    [8]
    Ozaktas H M, Arikan O, Kutay M A, et al. Digital computation of the fractional Fourier transform[J]. IEEE Transactions on Signal Processing, 1996, 44(9): 2141–2150. DOI: 10.1109/78.536672
    [9]
    Saxena R and Singh K. Fractional Fourier transform: A novel tool for signal processing[J]. Journal of the Indian Institute of Science, 2005, 85(1): 11–26.
    [10]
    Namias V. The fractional order Fourier transform and its application to quantum mechanics[J]. IMA Journal of Applied Mathematics, 1980, 25(3): 241–265. DOI: 10.1093/imamat/25.3.241
    [11]
    田瑞琦, 鲍庆龙, 王丁禾, 等. 基于FRFT与Keystone变换的运动目标参数估计算法[J]. 雷达学报, 2014, 3(5): 511–517. DOI: 10.3724/SP.J.1300.2014.14058

    Tian Rui-qi, Bao Qing-long, Wang Ding-he, et al. An algorithm for target parameter estimation based on fractional Fourier and Keystone transforms[J]. Journal of Radars, 2014, 3(5): 511–517. DOI: 10.3724/SP.J.1300.2014.14058
    [12]
    Almeida L B. The fractional Fourier transform and time-frequency representations[J]. IEEE Transactions on Signal Processing, 1994, 42(11): 3084–3091. DOI: 10.1109/78.330368
    [13]
    吴超楠. 基于分数阶傅里叶变换的高精度线性调频信号参数估计方法[D]. [硕士论文], 华南理工大学, 2014: 15–63

    Wu Chaonan. High-precision parameter estimation for LFM signal based on fractional Fourier transform[D]. [Master dissertation], South China University of Technology, 2014: 15–63
    [14]
    Schonhoff T A and Giordano A A. Detection and Estimation Theory and its Applications[M]. Upper Saddle River, NJ: Prentice Hall, 2006
    [15]
    艾越. 分置MIMO雷达多目标信号级定位算法研究[D]. [硕士论文], 电子科技大学, 2015: 19–23

    Ai Yue. Research of MIMO radar with widely separated antennas signal level multi-target localization[D]. [Master dissertation], University of Electronic Science and Technology of China, 2015: 19–23
    [16]
    Schultz R R and Stevenson R L. A Bayesian approach to image expansion for improved definition[J]. IEEE Transactions on Image Processing, 1994, 3(3): 233–242. DOI: 10.1109/83.287017
    [17]
    Sneath P H A and Sokal R R. Numerical taxonomy: The principles and practice of numerical classification[J]. Taxon, 1963, 12(5): 190–199.
  • 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(3023) PDF downloads(335) Cited by()
    Proportional views
    Related

    /

    DownLoad:  Full-Size Img  PowerPoint