Efficient 2-D Direction Finding Based on the Real-valued Subspace Linear Transformation with Nonuniform Circular Array

MENG Xiangtian; JING Zhehan; CAO Bingxia; SHA Minghui; ZHU Yingshen; YAN Fenggang

doi:10.11999/JEIT240188

Volume 46 Issue 11

Nov. 2024

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Article Navigation > Journal of Electronics & Information Technology > 2024 > 46(11): 4328-4334

MENG Xiangtian, JING Zhehan, CAO Bingxia, SHA Minghui, ZHU Yingshen, YAN Fenggang. Efficient 2-D Direction Finding Based on the Real-valued Subspace Linear Transformation with Nonuniform Circular Array[J]. Journal of Electronics & Information Technology, 2024, 46(11): 4328-4334. doi: 10.11999/JEIT240188

Citation:

MENG Xiangtian, JING Zhehan, CAO Bingxia, SHA Minghui, ZHU Yingshen, YAN Fenggang. Efficient 2-D Direction Finding Based on the Real-valued Subspace Linear Transformation with Nonuniform Circular Array[J]. Journal of Electronics & Information Technology, 2024, 46(11): 4328-4334. doi: 10.11999/JEIT240188

Citation:

MENG Xiangtian, JING Zhehan, CAO Bingxia, SHA Minghui, ZHU Yingshen, YAN Fenggang. Efficient 2-D Direction Finding Based on the Real-valued Subspace Linear Transformation with Nonuniform Circular Array[J]. Journal of Electronics & Information Technology, 2024, 46(11): 4328-4334. doi: 10.11999/JEIT240188

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Efficient 2-D Direction Finding Based on the Real-valued Subspace Linear Transformation with Nonuniform Circular Array

doi: 10.11999/JEIT240188 cstr: 32379.14.JEIT240188

1.
School of Information Science and Engineering, Harbin Institute of Technology(Weihai), Weihai 264209, China
2.
School of Electronics and Information Engineering, Harbin Institute of Technology, Harbin 150001, China
3.
Beijing Institute of Radio Measurement, Beijing 100854, China

Funds: The National Natural Science Foundation of China (62171150), Taishan Scholar Special Funding Project of Shandong Province (tsqn202211087), Shandong Provincial Natural Science Foundation (ZR2023MR091), The Aeronautical Science Foundation of China (2023Z037077002)

Received Date: 2024-03-20
Rev Recd Date: 2024-10-03

Available Online: 2024-10-15

Publish Date: 2024-11-01

Abstract

Abstract

The central symmetry based on the virtual array is a necessary fundamental assumption for the structure transformation of Uniform Circular Arrays (UCAs). In this paper, the virtual signal model for circular arrays is used to make an eigen analysis, and an efficient two-dimensional direction finding algorithm is proposed for arbitrary UCAs and Non Uniform Circular Arrays (NUCAs), where the structure transformation of linear arrays is avoided. As such, the Forward/Backward average of the Array Covariance Matrix (FBACM) and the sum-difference transformation method after separating the real and imaginary parts are both utilized to obtain the manifold and real-valued subspace with matching dimensions. Moreover, the linear relationship between the obtained real-valued subspace and the original complex-valued subspace is revealed, where the spatial spectrum is reconstructed without fake targets. The proposed method can be generalized to NUCAs, enhancing the adaptability of real-valued algorithms to circular array structures. Numerical simulations are applied to demonstrate that with significantly reduced complexity, the proposed method in this paper can provide similar performances and better angle resolution as compared to the traditional UCAs based on the mode-step. Meanwhile, the proposed method demonstrates high robustness with amplitude and phase errors in practical scenarios.
- Direction Of Arrival (DOA),
- Real-valued estimation,
- Circular array

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References(19)

References

[1]	CONG Jingyu, WANG Xianpeng, LAN Xiang, et al. A generalized noise reconstruction approach for robust DOA estimation[J]. IEEE Transactions on Radar Systems, 2023, 1: 382–394. doi: 10.1109/TRS.2023.3299184.
[2]	SHEN Ji, YI Jianxin, WAN Xianrong, et al. DOA estimation considering effect of adaptive clutter rejection in passive radar[J]. IEEE Transactions on Geoscience and Remote Sensing, 2022, 60: 5108913. doi: 10.1109/TGRS.2022.3141219.
[3]	WEN Fangqing, GUI Guan, GACANIN H, et al. Compressive sampling framework for 2D-DOA and polarization estimation in mmWave polarized massive MIMO systems[J]. IEEE Transactions on Wireless Communications, 2023, 22(5): 3071–3083. doi: 10.1109/TWC.2022.3215965.
[4]	ZHANG Zongyu, SHI Zhiguo, and GU Yujie. Ziv-zakai bound for DOAs estimation[J]. IEEE Transactions on Signal Processing, 2023, 71: 136–149. doi: 10.1109/TSP.2022.3229946.
[5]	马健钧, 魏少鹏, 马晖, 等. 基于ADMM的低仰角目标二维DOA估计算法[J]. 电子与信息学报, 2022, 44(8): 2859–2866. doi: 10.11999/JEIT210582. MA Jianjun, WEI Shaopeng, MA Hui, et al. Two-dimensional DOA estimation for low-angle target based on ADMM[J]. Journal of Electronics & Information Technology, 2022, 44(8): 2859–2866. doi: 10.11999/JEIT210582.
[6]	SCHMIDT R. Multiple emitter location and signal parameter estimation[J]. IEEE Transactions on Antennas and Propagation, 1986, 34(3): 276–280. doi: 10.1109/TAP.1986.1143830.
[7]	BARABELL A. Improving the resolution performance of eigenstructure-based direction-finding algorithms[C]. IEEE International Conference on Acoustics, Speech, and Signal Processing, Boston, USA, 1983: 336–339. doi: 10.1109/ICASSP.1983.1172124.
[8]	SWINDLEHURST A L, OTTERSTEN B, ROY R, et al. Multiple invariance ESPRIT[J]. IEEE Transactions on Signal Processing, 1992, 40(4): 867–881. doi: 10.1109/78.127959.
[9]	DAVIES D E N. A transformation between the phasing techniques required for linear and circular aerial arrays[J]. Proceedings of the Institution of Electrical Engineers, 1965, 112(11): 2041–2045. doi: 10.1049/piee.1965.0340.
[10]	MATHEWS C P and ZOLTOWSKI M D. Eigenstructure techniques for 2-D angle estimation with uniform circular arrays[J]. IEEE Transactions on Signal Processing, 1994, 42(9): 2395–2407. doi: 10.1109/78.317861.
[11]	BELLONI F and KOIVUNEN V. Unitary root-MUSIC technique for uniform circular array[C]. The 3rd IEEE International Symposium on Signal Processing and Information Technology, Darmstadt, Germany, 2003: 451–454. doi: 10.1109/ISSPIT.2003.1341155.
[12]	MATHEWS C P and ZOLTOWSKI M D. Performance analysis of the UCA-ESPRIT algorithm for circular ring arrays[J]. IEEE Transactions on Signal Processing, 1994, 42(9): 2535–2539. doi: 10.1109/78.317881.
[13]	WU Yuntao, AMIR L, JENSEN J R, et al. Joint pitch and DOA estimation using the ESPRIT method[J]. IEEE/ACM Transactions on Audio, Speech, and Language Processing, 2015, 23(1): 32–45. doi: 10.1109/taslp.2014.2367817.
[14]	闫锋刚, 沈毅, 刘帅, 等. 高效超分辨波达方向估计算法综述[J]. 系统工程与电子技术, 2015, 37(7): 1465–1475. doi: 10.3969/j.issn.1001-506X.2015.07.01. YAN Fenggang, SHEN Yi, LIU Shuai, et al. Overview of efficient algorithms for super-resolution DOA estimates[J]. Systems Engineering and Electronics, 2015, 37(7): 1465–1475. doi: 10.3969/j.issn.1001-506X.2015.07.01.
[15]	HUARNG K C and YEH C C. A unitary transformation method for angle-of-arrival estimation[J]. IEEE Transactions on Signal Processing, 1991, 39(4): 975–977. doi: 10.1109/78.80927.
[16]	YAN Fenggang, JIN Ming, LIU Shuai, et al. Real-valued MUSIC for efficient direction estimation with arbitrary array geometries[J]. IEEE Transactions on Signal Processing, 2014, 62(6): 1548–1560. doi: 10.1109/TSP.2014.2298384.
[17]	YAN Fenggang, YAN Xuewei, SHI Jun, et al. MUSIC-like direction of arrival estimation based on virtual array transformation[J]. Signal Processing, 2017, 139: 156–164. doi: 10.1016/j.sigpro.2017.04.017.
[18]	王兆彬, 巩朋成, 邓薇, 等. 联合协方差矩阵重构和ADMM的鲁棒波束形成[J]. 哈尔滨工业大学学报, 2023, 55(4): 64–71. doi: 10.11918/202107104. WANG Zhaobin, GONG Pengcheng, DENG Wei, et al. Robust beamforming by joint covariance matrix reconstruction and ADMM[J]. Journal of Harbin Institute of Technology, 2023, 55(4): 64–71. doi: 10.11918/202107104.
[19]	WILKES D M, MORGERA S D, NOOR F, et al. A hermitian toeplitz matrix is unitarily similar to a real toeplitz-plus-hankel matrix[J]. IEEE Transactions on Signal Processing, 1991, 39(9): 2146–2148. doi: 10.1109/78.134459.