Wide field-of-view direction finding with a millimeter wave arbitrary irregular array based on compressed sensing

被引:0
|
作者
Chen L. [1 ]
Ma W. [1 ]
Rao Z. [1 ]
Wang Y. [1 ]
机构
[1] School of Information Engineering, Nanchang University, Nanchang
关键词
Arbitrary irregular array; Compressed sensing; Direction finding; Millimetre wave; Sparsity; Wide field-of-view;
D O I
10.13245/j.hust.190912
中图分类号
学科分类号
摘要
Due to the short wavelength of millimeter wave, conventional passive direction finding method is difficult to realize wide filed-of-view direction finding.In order to solve the problem, a direction finding method with an arbitrary irregular array based on compressed sensing was proposed in this paper.Based on the principles of the aperture synthesis radiometry and the sparse characteristic of millimeter wave emitters, the system model and the measurement equations were established.The fundamental of adopting an arbitrary irregular array to realize wide field-of-view direction finding and its advantages were presented.Numeric simulations for the validation of the method, the characteristic of wide filed-of-view direction, and the feature of adopting arbitrary irregular arrays were carried out.Further, indoor experiments based on a prototype working at 8 mm band were carried out.The simulation and experimental results match well with the theoretical expectation, which shows the method can solve the problem of wide field-of-view direction finding. © 2019, Editorial Board of Journal of Huazhong University of Science and Technology. All right reserved.
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页码:67 / 71
页数:4
相关论文
共 12 条
  • [1] Wang X., Kong L., Kong F., Et al., Millimeter wave communication: a comprehensive survey, IEEE Communications Surveys & Tutorials, 20, 3, pp. 1616-1653, (2018)
  • [2] Lee J.H., Woo J.M., Method for obtaining three-and four-element array spacing for interferometer directionfinding system, IEEE Antennas & Wireless Propagation Letters, 15, pp. 897-900, (2016)
  • [3] Yan F., Jin M., Qiao X., Low-complexity DOA estimation based on compressed MUSIC and its performance analysis, IEEE Transactions on Signal Processing, 61, 8, pp. 1915-1930, (2013)
  • [4] Han K., Nehorai A., Jointly optimal design for mimo radar frequency-hopping waveforms using game theory, IEEE Transactions on Aerospace & Electronic Systems, 52, 2, pp. 809-820, (2016)
  • [5] Lukin K., Vyplavin P., Palamarchuk V., Et al., Millimeter-wave noise radar tomography, Proc of International Kharkiv Symposium on Physics and Engineering of Microwaves, Millimeter and Submillimeter, pp. 1-6, (2016)
  • [6] Donoho D., Compressed sensing, IEEE Transactions on Information Theory, 52, 4, pp. 1289-1306, (2006)
  • [7] Liu Q., Wang S., Ying L., Et al., Adaptive dictionary learning in sparse gradient domain for image recovery, IEEE Transactions on Image Processing, 22, 12, pp. 4652-4663, (2013)
  • [8] Das A., Hodgkiss W.S., Gerstoft P., Coherent multipath direction-of-arrival resolution using compressed sensing, IEEE Journal of Oceanic Engineering, pp. 1-13, (2016)
  • [9] Tan Z., Nehorai A., Sparse direction of arrival estimation using co-prime arrays with off-grid targets, IEEE Signal Processing Letters, 21, 1, pp. 26-29, (2013)
  • [10] Li J., Hu F., He F., Et al., Super-resolution RFI localization with compressive sensing in synthetic aperture interferometric radiometers, Proc of International Geoscience & Remote Sensing Symposium, pp. 4734-4737, (2015)