Journal
IEEE SENSORS JOURNAL
Volume 21, Issue 4, Pages 5282-5291Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/JSEN.2020.3034761
Keywords
Estimation; Direction-of-arrival estimation; Geometry; Antenna arrays; Mutual coupling; Discrete Fourier transforms; Covariance matrices; Sparse nested arrays; coprime displacement; DOA estimation; mutual coupling; DFT
Funding
- National Natural Science Foundation of China [61601167, 61971217, 61631020]
- Fundamental Research Funds for the Central Universities [NT2019013]
- Jiangsu Postdoctoral Science Foundation [2020Z013]
- China Postdoctoral Science Foundation [2020M681585]
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This paper discusses a new array geometry (SNACD) for DOA estimation, which combines the properties of nested array and coprime array, achieving good performance in both co-array and physical-array domains. The proposed scheme outperforms existing methods in terms of DOA estimation accuracy, angular resolution, and mutual coupling influence. Multiple simulations are provided to demonstrate the effectiveness of the approach.
Direction of arrival (DOA) estimation using new proposed array geometries named sparse nested arrays with coprime displacement (SNACD) is discussed in this paper. The SNACD has sparse subarrays with nested relationship, and the displacement between the subarrays is coprime to the inter-element spacing of the smaller subarray. This geometry can combine the properties of nested array and coprime array, which can simultaneously achieve virtual uniform array with large aperture in co-array domain and reduce the mutual coupling influence in physical-array domain. In the co-array domain, the coprime parameter estimations are separated into the virtual direction matrix and source vector, respectively. Based on this data model, several DOA estimation methods can be applied, like the spatial smooth multiple signal classification (SS-MUSIC) and atomic norm minimization based grid-less (ANM-GL) method, which both are robust to the grid mismatch problem. To further reduce the complexity, we proceed to propose a Discrete Fourier transform with offset compensation (DFT-OC) method, which requires neither eigenvalue decomposition nor sparse recovery. The final unique DOA estimation is achieved from the intersection of the coprime estimations, which are achieved with automatically pairing. Compared to coprime array and nested array based methods, the proposed scheme obtains better DOA estimation accuracy and higher angular resolution with mutual coupling influence. Multiple simulations are presented to verify the effectiveness of our approach.
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