Sparsity-Aware Noise Subspace Fitting for DOA Estimation
Abstract
:1. Introduction
2. Signal Model
2.1. Array Processing Model
2.2. OWNSF and Its Sparse Representation
3. The Proposed SANSF Algorithm for DOA Estimation
3.1. Sparsity-Aware Noise Subspace Fitting
3.2. About the Initialization
3.3. The Effect of Sparsity Enhancement
4. Numerical and Experimental Results
4.1. Root-Mean-Squared-Errors (RMSEs)
4.2. Resolution
4.2.1. Probability of Resolution
4.2.2. Histogram for 1D Closely Spaced Sources
4.2.3. Spatial Spectrum for 2D Closely Spaced Sources
4.3. Robustness to the Assumption of Uncorrelated Sources
4.4. Computational Complexity
4.5. DOA Tracking Results with Real Measured Ultrasonic Data
4.6. DOA Eestimation Results with Real Radar Data
5. Conclusions
Author Contributions
Funding
Conflicts of Interest
Appendix A
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Algorithms | MUSIC | MODE-ULA | WGMF | LIKES | SANSF |
---|---|---|---|---|---|
Start | 488 | 314 | 560 | 426 | 601 |
End | 789 | 809 | 680 | 847 | 715 |
Parameters | Tx Channel | Rx Channel | Start Frequency | Frequency Slope | ADC Samples | Sample Rate |
---|---|---|---|---|---|---|
Value | Tx1 | Rx1,2,3,4 | 77 GHz | 66.626 MHz/s | 256 | 5000 ksps |
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Zheng, C.; Chen, H.; Wang, A. Sparsity-Aware Noise Subspace Fitting for DOA Estimation. Sensors 2020, 20, 81. https://doi.org/10.3390/s20010081
Zheng C, Chen H, Wang A. Sparsity-Aware Noise Subspace Fitting for DOA Estimation. Sensors. 2020; 20(1):81. https://doi.org/10.3390/s20010081
Chicago/Turabian StyleZheng, Chundi, Huihui Chen, and Aiguo Wang. 2020. "Sparsity-Aware Noise Subspace Fitting for DOA Estimation" Sensors 20, no. 1: 81. https://doi.org/10.3390/s20010081
APA StyleZheng, C., Chen, H., & Wang, A. (2020). Sparsity-Aware Noise Subspace Fitting for DOA Estimation. Sensors, 20(1), 81. https://doi.org/10.3390/s20010081