Compressive Sampling of Polarimetric Doppler Weather Radar Processing Via Inverse Fast Fourier Transform
Polarimetric Doppler frequency-modulated continuous-wave weather radar produces a tremendous amount of data during the observation of atmospheric conditions. Using conventional signal processing method, the beat signals are sampled at Nyquist rate, so that the range signal can be reconstructed perfe...
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| Format: | Article |
| Language: | English |
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IEEE
2021-01-01
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| Series: | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/9435095/ |
| _version_ | 1818609389151453184 |
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| author | Rita Purnamasari Andriyan Bayu Suksmono Irma Zakia Ian Joseph Matheus Edward |
| author_facet | Rita Purnamasari Andriyan Bayu Suksmono Irma Zakia Ian Joseph Matheus Edward |
| author_sort | Rita Purnamasari |
| collection | DOAJ |
| description | Polarimetric Doppler frequency-modulated continuous-wave weather radar produces a tremendous amount of data during the observation of atmospheric conditions. Using conventional signal processing method, the beat signals are sampled at Nyquist rate, so that the range signal can be reconstructed perfectly. We propose compressive sampling (CS) technique to sample and reduce the data simultaneously by exploring the sparsity of the beat signal in transform domain. Reducing the number of the beat signal and the transform coefficients are natural choices, because sparse signals will be obtained by inverse Fourier transforming the beat signals. The proposed techniques are evaluated by constructing the plan position indicator of reflectivity and mean Doppler velocity measurements from real weather polarimetric data. Compared to the conventional method, the CS polarimetric Doppler processing significantly reduce the number of the data while pertaining important weather information. We show that the proposed method works properly to quantify and classify the precipitation, mainly when the number of the samples is above 25% of its original. |
| first_indexed | 2024-12-16T14:57:45Z |
| format | Article |
| id | doaj.art-30bbe8f3c0c74b0db78b6f64c19fac9b |
| institution | Directory Open Access Journal |
| issn | 2151-1535 |
| language | English |
| last_indexed | 2024-12-16T14:57:45Z |
| publishDate | 2021-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing |
| spelling | doaj.art-30bbe8f3c0c74b0db78b6f64c19fac9b2022-12-21T22:27:23ZengIEEEIEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing2151-15352021-01-01145269528410.1109/JSTARS.2021.30812659435095Compressive Sampling of Polarimetric Doppler Weather Radar Processing Via Inverse Fast Fourier TransformRita Purnamasari0https://orcid.org/0000-0002-3131-6345Andriyan Bayu Suksmono1Irma Zakia2https://orcid.org/0000-0003-1556-3589Ian Joseph Matheus Edward3Telecommunication Engineering Group, School of Electrical Engineering and Informatics, Institut Teknologi Bandung (ITB), Bandung, IndonesiaTelecommunication Engineering Group, School of Electrical Engineering and Informatics, Institut Teknologi Bandung (ITB), Bandung, IndonesiaTelecommunication Engineering Group, School of Electrical Engineering and Informatics, Institut Teknologi Bandung (ITB), Bandung, IndonesiaTelecommunication Engineering Group, School of Electrical Engineering and Informatics, Institut Teknologi Bandung (ITB), Bandung, IndonesiaPolarimetric Doppler frequency-modulated continuous-wave weather radar produces a tremendous amount of data during the observation of atmospheric conditions. Using conventional signal processing method, the beat signals are sampled at Nyquist rate, so that the range signal can be reconstructed perfectly. We propose compressive sampling (CS) technique to sample and reduce the data simultaneously by exploring the sparsity of the beat signal in transform domain. Reducing the number of the beat signal and the transform coefficients are natural choices, because sparse signals will be obtained by inverse Fourier transforming the beat signals. The proposed techniques are evaluated by constructing the plan position indicator of reflectivity and mean Doppler velocity measurements from real weather polarimetric data. Compared to the conventional method, the CS polarimetric Doppler processing significantly reduce the number of the data while pertaining important weather information. We show that the proposed method works properly to quantify and classify the precipitation, mainly when the number of the samples is above 25% of its original.https://ieeexplore.ieee.org/document/9435095/Compressive sampling (CS)frequency modulated continuous wave (FMCW)inverse fast Fourier transform (IFFT)polarimetric Doppler weather radar (PDWR)sparse representationweather radar |
| spellingShingle | Rita Purnamasari Andriyan Bayu Suksmono Irma Zakia Ian Joseph Matheus Edward Compressive Sampling of Polarimetric Doppler Weather Radar Processing Via Inverse Fast Fourier Transform IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing Compressive sampling (CS) frequency modulated continuous wave (FMCW) inverse fast Fourier transform (IFFT) polarimetric Doppler weather radar (PDWR) sparse representation weather radar |
| title | Compressive Sampling of Polarimetric Doppler Weather Radar Processing Via Inverse Fast Fourier Transform |
| title_full | Compressive Sampling of Polarimetric Doppler Weather Radar Processing Via Inverse Fast Fourier Transform |
| title_fullStr | Compressive Sampling of Polarimetric Doppler Weather Radar Processing Via Inverse Fast Fourier Transform |
| title_full_unstemmed | Compressive Sampling of Polarimetric Doppler Weather Radar Processing Via Inverse Fast Fourier Transform |
| title_short | Compressive Sampling of Polarimetric Doppler Weather Radar Processing Via Inverse Fast Fourier Transform |
| title_sort | compressive sampling of polarimetric doppler weather radar processing via inverse fast fourier transform |
| topic | Compressive sampling (CS) frequency modulated continuous wave (FMCW) inverse fast Fourier transform (IFFT) polarimetric Doppler weather radar (PDWR) sparse representation weather radar |
| url | https://ieeexplore.ieee.org/document/9435095/ |
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