An online SAR focusing framework using state-space models processes raw data line-by-line with 70x lower latency and 130x lower memory than block-based DSP while supporting downstream tasks.
Cooley and John W
2 Pith papers cite this work. Polarity classification is still indexing.
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Improved pPXF uses analytic Fourier transforms of Gauss-Hermite functions for accurate convolution, providing reliable velocities even when σ is much less than the sampling ΔV.
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Learning to Focus Synthetic Aperture Radar On-line with State-Space Models
An online SAR focusing framework using state-space models processes raw data line-by-line with 70x lower latency and 130x lower memory than block-based DSP while supporting downstream tasks.
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Improving the full spectrum fitting method: accurate convolution with Gauss-Hermite functions
Improved pPXF uses analytic Fourier transforms of Gauss-Hermite functions for accurate convolution, providing reliable velocities even when σ is much less than the sampling ΔV.