Improved unfolded coprime array subject to motion for DOA estimation: augmented consecutive synthetic difference co-array

Penghui Ma; Jianfeng Li; Xiaofei Zhang; Gaofeng Zhao

Improved unfolded coprime array subject to motion for DOA estimation: augmented consecutive synthetic difference co-array

View Fulltext

Author(s): Penghui Ma^{1, 2} ; Jianfeng Li^{1, 2} ; Xiaofei Zhang^{1, 2} ; Gaofeng Zhao^{1, 2}
- Affiliations: 1: Key Laboratory of Dynamic Cognitive System of Electromagnetic Spectrum Space (Nanjing University of Aeronautics and Astronautics) , Ministry of Industry and Information Technology , Nanjing 211106 , People's Republic of China ;
  2: College of Electronic Information Engineering, Nanjing University of Aeronautics and Astronautics , Nanjing 211106 , People's Republic of China
Source: Volume 14, Issue 10, 18 December 2020, p. 823 – 836
DOI: 10.1049/iet-spr.2020.0200 , Print ISSN 1751-9675, Online ISSN 1751-9683

Received 30/04/2020, Accepted 06/01/2021, Revised 04/12/2020, Published 18/01/2021

Direction of arrival (DOA) estimation using the improved unfolded coprime array (IUFCA) subject to array motion isdiscussed in this study. Unfolded coprime array (UFCA) consists of two uniform linear subarrays, and the two subarrays are arranged at different sides of theaxis, which leads to a large number of holes in the difference co-array (DCA). With array motion and DCA synthesis,part of the holes can be filled, but there are still holes in the center which lead to the virtual arrays separated.By analyzing the hole positions in the synthetic DCA generated by UFCA motion, the authors improve the originalUFCA by relocating some physical elements, then the two dominantconsecutive DCA segments in the positive and negative sides can be connected. The expression of synthetic DCA is analyzed, and the closed-form expression of theuniform degree of freedom (uDOF) subject to IUFCA motion is studied. Simulation results show that IUFCA motion can obtain a largenumber of uDOFs, which leads to better DOA estimation performance and more identifiable signals compared with existingcoprime array configurations.

References

1. 1)
  - 18. Ramirez, J., Krolik, J.L.: ‘Synthetic aperture processing for passive co-prime linear sensor arrays’, Digit. Signal Process., 2017, 61, pp. 62–75.
2. 2)
  - 22. Jiang, J., Sun, Z., Duan, F., et al: ‘Synthesis and modification of cetacean tonal sounds for underwater bionic covert detection and communication’, IEEE Access, 2020, 8, pp. 119980–119994.
3. 3)
  - 6. Zhou, C., Gu, Y., He, S., et al: ‘A robust and efficient algorithm for coprime array adaptive beamforming’, IEEE Trans. Veh. Technol., 2018, 67, (2), pp. 1099–1112.
4. 4)
  - 2. Hou, Y., Wang, W.: ‘Active frequency diverse array counteracting interferometry-based doa reconnaissance’, IEEE Antennas Wirel. Propag. Lett., 2019, 18, (9), pp. 1922–1925.
5. 5)
  - 10. Zheng, W., Zhang, X., Gong, P., et al: ‘Doa estimation for coprime linear arrays: an ambiguity-free method involving full dofs’, IEEE Commun. Lett., 2018, 22, (3), pp. 562–565.
6. 6)
  - 23. Thomson, D.J.M., Dosso, S.E., Barclay, D.R.: ‘Modeling auv localization error in a long baseline acoustic positioning system’, IEEE J. Ocean. Eng., 2018, 43, (4), pp. 955–968.
7. 7)
  - 16. Raza, A., Liu, W., Shen, Q.: ‘Thinned coprime array for second-order difference co-array generation with reduced mutual coupling’, IEEE Trans. Signal Process., 2019, 67, (8), pp. 2052–2065.
8. 8)
  - 13. Zheng, W., Zhang, X., Li, J., et al: ‘Extensions of co-prime array for improved doa estimation with hole filling strategy’, IEEE Sens. J., 2021, 21, pp. 6724–6732.
9. 9)
  - 17. Wang, X., Wang, X.: ‘Hole identification and filling in k-times extended co-prime arrays for highly efficient doa estimation’, IEEE Trans. Signal Process., 2019, 67, (10), pp. 2693–2706.
10. 10)
  - 19. Qin, G., Amin, M.G., Zhang, Y.D.: ‘Doa estimation exploiting sparse array motions’, IEEE Trans. Signal Process., 2019, 67, (11), pp. 3013–3027.
11. 11)
  - 20. Qin, G., Amin, M.G., Zhang, Y.D.: ‘Analysis of coprime arrays on moving platform’. ICASSP 2019–2019 IEEE Int. Conf. on Acoustics, Speech and Signal Processing (ICASSP), Brighton, United Kingdom, 2019, pp. 4205–4209.
12. 12)
  - 14. Li, J., Zhang, X.: ‘Direction of arrival estimation of quasi-stationary signals using unfolded coprime array’, IEEE Access, 2017, 5, pp. 6538–6545.
13. 13)
  - 4. Guo, M., Zhang, Y.D., Chen, T.: ‘Doa estimation using compressed sparse array’, IEEE Trans. Signal Process., 2018, 66, (15), pp. 4133–4146.
14. 14)
  - 28. Pal, P., Vaidyanathan, P.P.: ‘Nested arrays: a novel approach to array processing with enhanced degrees of freedom’, IEEE Trans. Signal Process., 2010, 58, (8), pp. 4167–4181.
15. 15)
  - 9. Vaidyanathan, P.P., Pal, P.: ‘Sparse sensing with co-prime samplers and arrays’, IEEE Trans. Signal Process., 2011, 59, (2), pp. 573–586.
16. 16)
  - 25. Pal, P., Vaidyanathan, P.P.: ‘Coprime sampling and the music algorithm’. 2011 Digital Signal Processing and Signal Processing Education Meeting (DSP/SPE), Sedona AZ, 2011, pp. 289–294.
17. 17)
  - 29. Cao, R., Liu, B., Gao, F., et al: ‘A low-complex one-snapshot doa estimation algorithm with massive ula’, IEEE Commun. Lett., 2017, 21, (5), pp. 1071–1074.
18. 18)
  - 5. Zheng, G., Tang, J., Yang, X.: ‘Esprit and unitary esprit algorithms for coexistence of circular and noncircular signals in bistatic mimo radar’, IEEE Access, 2016, 4, pp. 7232–7240.
19. 19)
  - 8. Zheng, W., Zhang, X., Wang, Y., et al: ‘Padded coprime arrays for improved doa estimation: exploiting hole representation and filling strategies’, IEEE Trans. Signal Process., 2020, 68, pp. 4597–4611.
20. 20)
  - 11. Li, J., Wang, F., Jiang, D.: ‘Direction of arrival estimation using sum co-array of coprime arrays’. 2017 Int. Applied Computational Electromagnetics Society Symp. (ACES), Suzhou, 2017, pp. 1–2.
21. 21)
  - 12. Liu, C., Vaidyanathan, P.P.: ‘Optimizing minimum redundancy arrays forrobustness’. 2018 52nd Asilomar Conf. on Signals, Systems, and Computers, Pacific Grove, USA, 2018, pp. 79–83.
22. 22)
  - 24. Khoa, X., Rong, Y., He, Z.: ‘A frequency domain equalizer for amplify-and-forward underwater acoustic relay communication systems’. 2013 9th Int. Conf. on Information, Communications & Signal Processing, Tainan, 2013, pp. 1–4.
23. 23)
  - 21. Qin, G., Amin, M.G.: ‘Optimum sparse array configuration for doa estimation on moving platforms’, Digit. Signal Process., 2020, 105, p. 102685.
24. 24)
  - 26. Li, J., Li, Y., Zhang, X.: ‘Two-dimensional off-grid doa estimation using unfolded parallel coprime array’, IEEE Commun. Lett., 2018, 22, (12), pp. 2495–2498.
25. 25)
  - 3. Shaikh, A.H., Dang, X., Ahmed, T., et al: ‘New transmit-receive array configurations for the mimo radar with enhanced degrees of freedom’, IEEE Commun. Lett., 2020, 24, (7), pp. 1534–1538.
26. 26)
  - 27. Zhou, C., Gu, Y., Fan, X., et al: ‘Direction-of-arrival estimation for coprime array via virtual array interpolation’, IEEE Trans. Signal Process., 2018, 66, (22), pp. 5956–5971.
27. 27)
  - 15. Zheng, W., Zhang, X., Wang, Y., et al: ‘Extended coprime array configuration generating large-scale antenna co-array in massive mimo system’, IEEE Trans. Veh. Technol., 2019, 68, (8), pp. 7841–7853.
28. 28)
  - 7. Liu, C., Vaidyanathan, P.P.: ‘Remarks on the spatial smoothing step in coarray music’, IEEE Signal Process. Lett., 2015, 22, (9), pp. 1438–1442.
29. 29)
  - 1. Li, C., Gan, L., Ling, C.: ‘Coprime sensing via Chinese remaindering over quadratic fields—part i: array designs’, IEEE Trans. Signal Process., 2019, 67, (11), pp. 2898–2910.
30. 30)
  - 30. Qin, S., Zhang, Y.D., Amin, M.G.: ‘Generalized coprime array configurations for direction-of-arrival estimation’, IEEE Trans. Signal Process., 2015, 63, (6), pp. 1377–1390.

Login

Not registered yet?

Share

Tools

Login to add to favourites

Key

Improved unfolded coprime array subject to motion for DOA estimation: augmented consecutive synthetic difference co-array

References

Related content