2D DOA and Polarization Estimation Using Parallel Synthetic Coprime Array of Non-Collocated EMVSs
Abstract
:1. Introduction
- (a)
- Due to a shared subarray and the non-collocated two-component EMVSs, the PSC-PSA can save at least half the number of antennas compared with the existing arrays in the case of a similar aperture and DOF in the coarray domain. The Cramér–Rao bound (CRB) derivation then shows that the former can provide better estimation performance with the same number of antennas.
- (b)
- Mutual coupling in the physical array domain can be efficiently reduced by spatial separation of antennas and extended displacements between subarrays. The separated antennas along the subarray direction are different array elements for IPC reduction. The displacements are extended in 2D (e.g., x- and y-axes) for mitigating IEC and further suppressing IPC.
- (c)
- Due to the array configuration, the polarization phase difference only exists in phase for one item in the 2D polarization domain, and then angle information can be inserted in phase for the other one. In this case, a block-sparse model is derived to achieve multi-parameter separation. The 1D sparse reconstruction-based method is then only used once to obtain multi-parameter estimation with automatic pair-matching, which avoids huge complexity.
2. Preliminaries
2.1. Polarized Signal Model
2.2. Difference Coarray
2.3. Mutual Coupling Model
3. Proposed Array
3.1. PSC-PSA
3.2. Mutual Coupling Analysis
- (a)
- Generally, the first three coefficients dominate the effect of mutual coupling for nonuniform scalar–vector arrays [18], i.e., , , and . In this case, for the same number of antennas W, the number of mutual coupling coefficients for the existing arrays is at least , while that for the proposed array is reduced to at most 12 due to the shared subarray and displacements between subarrays in both the x- and y-axes. This shows that the PSC-PSA can eliminate mutual coupling with the decreased number of coupling coefficients.
- (b)
- On the other hand, considering both the displacements and spatial separation between differently polarized antennas along the x- and y-axes, the values of coefficients for the PSC-PSA are much smaller than those (e.g., or ) for the existing arrays. This reflects that the former can mitigate mutual coupling by decreasing the values of the coupling coefficients.
4. 2D DOA and Polarization Estimation
4.1. Block Sparse Model
4.2. BCS-Based Estimation Method with 1D Sparse Reconstruction
4.3. Computational Complexity
5. CRB
6. Simulation Results
6.1. Mutual Coupling Ratio
6.2. Scatter Diagrams
6.3. RMSE
7. Conclusions
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
Appendix A
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Subarray 1 | Subarray 2 | ||||||
---|---|---|---|---|---|---|---|
j = 1,4,7 10,13,16 | j = 2,5,8 11,14,17 | j = 3,6,9 12,15,18 | j = 19,23,27 31,35,39 | j = 20,24,28 32,36,40 | j = 21,25,29 33,37,41 | j = 22,26,30 34,38,42 | |
(0,0) | (0,4d) | (0,8d) | (d,0) | (d,) | (d,) | (d,) |
With Mutual Coupling | Without Mutual Coupling | |||
---|---|---|---|---|
2D DOA Estimation | Polarization Estimation | 2D DOA Estimation | Polarization Estimation | |
TPC-PSA | ||||
PCP-PSA | ||||
Proposed | ||||
Proposed with strong mutual coupling | - | - |
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Yang, Y.; Shan, M.; Jiang, G. 2D DOA and Polarization Estimation Using Parallel Synthetic Coprime Array of Non-Collocated EMVSs. Remote Sens. 2024, 16, 3004. https://doi.org/10.3390/rs16163004
Yang Y, Shan M, Jiang G. 2D DOA and Polarization Estimation Using Parallel Synthetic Coprime Array of Non-Collocated EMVSs. Remote Sensing. 2024; 16(16):3004. https://doi.org/10.3390/rs16163004
Chicago/Turabian StyleYang, Yunlong, Mengru Shan, and Guojun Jiang. 2024. "2D DOA and Polarization Estimation Using Parallel Synthetic Coprime Array of Non-Collocated EMVSs" Remote Sensing 16, no. 16: 3004. https://doi.org/10.3390/rs16163004