Atmospheric radar imaging improvements using compressed sensing and MIMO

DOI10.1007/978-3-031-09745-4_12zbMath1504.94009OpenAlexW4312546874MaRDI QIDQ2106492

Tobias Weber, Juan Miguel Urco, Jeremy Olaore Aweda, Jorge Luis Chau

Publication date: 14 December 2022

Full work available at URL: https://doi.org/10.1007/978-3-031-09745-4_12

zbMATH Keywords

Kelvin-Helmholtz instabilitypolar mesospheric summer echoes

Mathematics Subject Classification ID

Signal theory (characterization, reconstruction, filtering, etc.) (94A12) Image processing (compression, reconstruction, etc.) in information and communication theory (94A08)

Uses Software

• JPEG2000

Cites Work

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• Range Compression and Waveform Optimization for MIMO Radar: A CramÉr–Rao Bound Based Study
• Best Basis Compressed Sensing
• Sparse Recovery of Nonnegative Signals With Minimal Expansion
• Recursive Recovery of Sparse Signal Sequences From Compressive Measurements: A Review
• For most large underdetermined systems of linear equations the minimal 𝓁₁‐norm solution is also the sparsest solution
• Stable signal recovery from incomplete and inaccurate measurements
• Optimal binary sequences for spread spectrum multiplexing (Corresp.)
• Polyphase codes with good periodic correlation properties (Corresp.)
• Bandelet Image Approximation and Compression

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