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Warianty tytułu
Języki publikacji
Abstrakty
Regular fully filled antenna arrays have been widely used in direction of arrival (DOA) estimation. However, practical implementation of these arrays is rather complex and their resolutions are limited to the beamwidth of the array pattern. Therefore, higher resolution and simpler methods are desirable. In this paper, the compressed sensing method is first applied to an initial fully filled array to randomly select the most prominent and effective elements which are used to form the sparse array. To keep the dimension of the sparse array equal to that of the fully filled array, the first and the last elements were excluded from the sparseness process. In addition, some constraints on the sparse spectrum are applied to increase estimation accuracy. The optimization problem is then solved iteratively using the iterative reweighted l1 norm. Finally, a simple searching algorithm is used to detect peaks in the spectrum solution that correspond to the directions of the arriving signals. Compared with the existing scanned beam methods, such as the minimum variance distortionless response (MVDR) technique, and with subspace approaches, such as multiple signal classification (MUSIC) and ESPIRT algorithms, the proposed sparse array method offers better performance even with a lower number of array elements and in severely noisy environments. Effectiveness of the proposed sparse array method is verified via computer simulations.
Słowa kluczowe
Rocznik
Tom
Strony
8--14
Opis fizyczny
Bibliogr. 21 poz., rys.
Twórcy
autor
- College of Electronics Engineering, Ninevah University, Mosul, Iraq
Bibliografia
- [1] M. Guo, Y. D. Zhang, and T. Chen, „DOA estimation using compressed sparse array", IEEE Trans. on Sig. Process., vol. 66, no. 15, pp. 4133-4146, 2018 (DOI: 10.1109/TSP.2018.2847645).
- [2] P. Gong, X. Zhang, and T. Ahmed, „Computationally efficient DOA estimation for coprime linear array: A successive signal subspace fitting algorithm", Int. J. of Electron., vol. 107, no. 8, pp. 1216-1238, 2020 (DOI: 10.1080/00207217.2020.1726485).
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- [4] M. Carlin, P. Rocca, G. Oliveri, F. Viani, and A. Massa, „Directions-of-arrival estimation through Bayesian compressive sensing strategies", IEEE Trans. on Antenn. Propag., vol. 61, no. 7, pp. 3828-3838, 2013 (DOI: 10.1109/TAP.2013.2256093).
- [5] A. D. Lonkeng and J. Zhuang, „Two-dimensional DOA estimation using arbitrary arrays for massive MIMO systems", Int. J. of Antenn. and Propag., vol. 2017, Article ID 6794920, 2017 (DOI: 10.1155/2017/6794920).
- [6] A. B. Gershman, M. Rubsamen, and M. Pesavento, „One- and twodimensional direction-of-arrival estimation: an overview of searchfree techniques", Sig. Process., vol. 90, no. 5, pp. 1338-1349, 2010 (DOI: 10.1016/j.sigpro.2009.12.008).
- [7] T. C. Yang, „Deconvolved conventional beamforming for a horizontal line array", IEEE J. of Oceanic Engin., vol. 43, no. 1, pp. 160-172, 2018 (DOI: 10.1109/JOE.2017.2680818).
- [8] J. Capon, „High-resolution frequency-wavenumber spectrum analysis", Proc. of the IEEE, vol. 57, no. 8, pp. 1408-1418, 1969 (DOI: 10.1109/PROC.1969.7278).
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- [10] R. Roy and T. Kailath, „ESPRIT-estimation of signal parameters via rotational invariance techniques", IEEE Trans. on Sig. Process., vol. 37, no. 7, pp. 984-995, 1989 (DOI: 10.1109/29.32276).
- [11] X. Fan, L. Pang, P. Shi, G. Li, and X. Zhang, „Application of bee evolutionary genetic algorithm to maximum likelihood direction-ofarrival estimation", Mathem. Probl. in Engin., vol. 2019, Article ID 6035870, 2019 (DOI: 10.1155/2019/6035870).
- [12] H. Chen, S. Li, J. Liu, F. Liu, and M. Suzuki, „A novel modification of PSO algorithm for SML estimation of DOA", Sensors, vol. 16, no. 12, 2016 (DOI: 10.3390/s16122188).
- [13] S. Zhao, Y. S. Shmaliy, and C. K. Ahn, „Iterative maximum likelihood FIR estimation of dynamic systems with improved robustness", IEEE/ASME Trans. on Mechatron., vol. 23, no. 3, pp. 1467-1476, 2018 (DOI: 10.1109/TMECH.2018.2820075).
- [14] K. H. Sayidmarie and J. R. Mohammed, „Performance of a wide angle and wideband nulling method for phased arrays", Progr. In Electromag. Res. M, vol. 33, pp. 239-249, 2013 (DOI: 10.2528/PIERM13100603).
- [15] J. R. Mohammed, „Design of printed Yagi antenna with additional driven element for WLAN applications", Progr. in Electromag. Res. C, vol. 37, pp. 67-81, 2013 (DOI: 10.2528/PIERC12121201).
- [16] J. R. Mohammed, „Element selection for optimized multi-wide nulls in almost uniformly excited arrays", IEEE Antenn. and Wirel. Propag. Lett., vol. 17, no. 4, pp. 629-632, 2018 (DOI: 10.1109/LAWP.2018.2807371).
- [17] J. R. Mohammed and K. H. Sayidmarie, „Sidelobe cancellation for uniformly excited planar array antennas by controlling the side elements", IEEE Antenn. and Wirel. Propag. Lett., vol. 13, pp. 987-990, 2014 (DOI: 10.1109/LAWP.2014.2325025).
- [18] J. Zhang, Z. Duan, Y. Zhang, and J. Liang, „Compressive sensing approach for DOA estimation based on sparse arrays in presence of mutual coupling", in Communications, Signal Processing, and Systems. Proceedings of the 8th International Conference on Communications, Signal Processing, and Systems, Q. Liang et al., Eds. Lecture Notes in Electrical Engineering, vol. 516. Springer, 2020 (DOI: 10.1007/978-981-13-6504-1 151).
- [19] H. Li, C. Wang, and X. Zhu, „Compressive sensing for high resolution direction-of-arrival estimation via iterative optimization on sensing matrix", Int. J. of Antenn. and Propag., vol. 2015, no. 1, Article ID 713930, 2015 (DOI: 10.1155/2015/713930).
- [20] S. F. Cotter, B. D. Rao, K. Engan, and K. Kreutz-Delgado, „Sparse solutions to linear inverse problems with multiple measurement vectors", IEEE Trans. on Sig. Process., vol. 53, no. 7, pp. 2477-2488, 2005 (DOI: 10.1109/TSP.2005.849172).
- [21] I. F. Gorodnitsky and B. D. Rao, „Sparse signal reconstruction from limited data using FOCUSS: A re-weighted minimum norm algorithm", IEEE Trans. on Sig. Process., vol. 45, no. 3, pp. 600-616, 1997 (DOI: 10.1109/78.558475).
Uwagi
Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2021).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-ec6122cf-29a2-451b-b9b0-0b626d6cf382