Computer vision quickly identifies radio signals with unlimited accuracy

A seminal component of systems thinking is the application of an advanced technology in one domain to solve a challenging problem in a different domain. This article introduces a method of using advanced computer vision to solve the challenging signal processing problem of specific emitter identification. A one-dimensional signal is sampled; those samples are transformed into to two-dimensional images by computing a bispectrum; those images are evaluated using advanced computer vision; and the results are statistically combined until any user-selected level of classification accuracy is obtained. In testing on a published DARPA challenge dataset, for every eight additional signal samples taken from a candidate signal (out of many thousands), classification error decreases by an entire order of magnitude.

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Publication Details

Journal
Scientific Reports
Published
2024-09-09
DOI
https://doi.org/10.1038/s41598-024-72023-9
Citations
1
Primary Topic
Wireless Signal Modulation Classification
Type
article
Field-Weighted Citation Impact
0.35
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article

Computer vision quickly identifies radio signals with unlimited accuracy

Michael C. Kleder
1 citations
Scientific Reports
Wireless Signal Modulation Classification
0.35
article

Computer vision quickly identifies radio signals with unlimited accuracy

Michael C. Kleder
article en
1 citations

Abstract

A seminal component of systems thinking is the application of an advanced technology in one domain to solve a challenging problem in a different domain. This article introduces a method of using advanced computer vision to solve the challenging signal processing problem of specific emitter identification. A one-dimensional signal is sampled; those samples are transformed into to two-dimensional images by computing a bispectrum; those images are evaluated using advanced computer vision; and the results are statistically combined until any user-selected level of classification accuracy is obtained. In testing on a published DARPA challenge dataset, for every eight additional signal samples taken from a candidate signal (out of many thousands), classification error decreases by an entire order of magnitude.

Scientific ReportsVol. 14(1)
Virginia Tech (US)
Openalex Percentile: Top 34%
Wireless Signal Modulation Classification
0.35
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