Multiple snapshot grid free compressive beamforming.

Area of Science:

• Signal Processing
• Array Signal Processing
• Electromagnetics

Background:

• Compressive Sensing (CS) offers efficient, high-resolution Direction-of-Arrival (DOA) estimation.
• Conventional CS methods face challenges like basis mismatch and instability with single snapshots.

Purpose of the Study:

• Propose a grid-free CS based DOA estimation technique using sequential multiple snapshots.
• Address limitations of conventional CS, including basis mismatch and estimate stability.

Main Methods:

• Implemented a grid-free CS approach utilizing sequential multiple snapshot data.
• Employed the group total variation norm for sparsity pattern imposition across snapshots.
• Utilized Singular Value Decomposition (SVD) to reduce computational complexity for extensive snapshot data.

Main Results:

• The proposed method achieves high-resolution DOA estimation, even for coherent sources.
• Successfully avoids the basis mismatch problem inherent in traditional CS techniques.
• Multiple snapshot processing yields stable estimates compared to single snapshot methods.

Conclusions:

• The grid-free, multiple-snapshot CS method provides a robust and accurate solution for DOA estimation.
• This technique offers significant advantages over conventional CS, particularly in scenarios with coherent signals and computational constraints.