Radar and Communications Source Separation via Sparse Time-Frequency Estimation

With recent trends in radio frequency (RF) spectrum policy, it is likely that future RF spectral environments will consist of multiple proximate (possibly uncooperative) users operating in the same frequency band to improve spectral efficiency. Therefore, RF processing will need to estimate and isolate the desired signal information in the presence of in-band interference. Here, a sparse estimation procedure is proposed to estimate radar backscatter in the presence of communications interference without prior knowledge of the communications modulation. The communications signal is modeled via a superposition of time-frequency basis functions to estimate (and isolate) the interference in time and frequency. A simulated example is provided that demonstrates the signal isolation performance.

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Publication Details

Published
2024-10-21
DOI
https://doi.org/10.1109/radar58436.2024.10993726
Citations
1
Primary Topic
Speech and Audio Processing
Type
article
Field-Weighted Citation Impact
0.35

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article

Radar and Communications Source Separation via Sparse Time-Frequency Estimation

Patrick M. McCormick, Faris Ahmed El-Katri
1 citations
Speech and Audio Processing
0.35
article

Radar and Communications Source Separation via Sparse Time-Frequency Estimation

Patrick M. McCormick, Faris Ahmed El-Katri
article en
1 citations

Abstract

With recent trends in radio frequency (RF) spectrum policy, it is likely that future RF spectral environments will consist of multiple proximate (possibly uncooperative) users operating in the same frequency band to improve spectral efficiency. Therefore, RF processing will need to estimate and isolate the desired signal information in the presence of in-band interference. Here, a sparse estimation procedure is proposed to estimate radar backscatter in the presence of communications interference without prior knowledge of the communications modulation. The communications signal is modeled via a superposition of time-frequency basis functions to estimate (and isolate) the interference in time and frequency. A simulated example is provided that demonstrates the signal isolation performance.

University of Kansas (US)
Advanced Research Projects Agency
Openalex Percentile: Top 38%
Speech and Audio Processing
0.35
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Radar and Communications Source Separation via Sparse Time-Frequency Estimation — Patrick M. McCormick, Faris Ahmed El-Katri · (2024) | TGRS Research Map | TGRS