A fast and accurate chirp rate estimation algorithm based on the fractional Fourier transform. Serbes, A. & Aldimashki, O. In 2017 25th European Signal Processing Conference (EUSIPCO), pages 1105-1109, Aug, 2017.
![A fast and accurate chirp rate estimation algorithm based on the fractional Fourier transform [pdf]](https://bibbase.org/img/filetypes/pdf.svg "pdf")
Paper doi abstract bibtex
Paper doi abstract bibtex In this work, a fast and accurate chirp-rate estimation algorithm is presented. The algorithm is based on the fractional Fourier transform. It is shown that utilization of the golden section search algorithm to find the maximum magnitude of the fractional Fourier transform domains not only accelerates the process, but also increases the accuracy in a noisy environment. Simulation results validate the proposed algorithm and show that the accuracy of parameter estimation nearly achieves the Cramer-Rao lower bound for SNR values as low as -7dB.
@InProceedings{8081379,
author = {A. Serbes and O. Aldimashki},
booktitle = {2017 25th European Signal Processing Conference (EUSIPCO)},
title = {A fast and accurate chirp rate estimation algorithm based on the fractional Fourier transform},
year = {2017},
pages = {1105-1109},
abstract = {In this work, a fast and accurate chirp-rate estimation algorithm is presented. The algorithm is based on the fractional Fourier transform. It is shown that utilization of the golden section search algorithm to find the maximum magnitude of the fractional Fourier transform domains not only accelerates the process, but also increases the accuracy in a noisy environment. Simulation results validate the proposed algorithm and show that the accuracy of parameter estimation nearly achieves the Cramer-Rao lower bound for SNR values as low as -7dB.},
keywords = {chirp modulation;Fourier transforms;parameter estimation;search problems;fractional Fourier transform;golden section search algorithm;parameter estimation;chirp rate estimation algorithm;noise figure 7.0 dB;Chirp;Signal processing algorithms;Time-frequency analysis;Fourier transforms;Noise measurement;Signal to noise ratio;Chirp signals;fractional Fourier transform;chirp rate;golden section search},
doi = {10.23919/EUSIPCO.2017.8081379},
issn = {2076-1465},
month = {Aug},
url = {https://www.eurasip.org/proceedings/eusipco/eusipco2017/papers/1570342282.pdf},
}Downloads: 0
{"_id":"vZcywcqu79KQ8SZBW","bibbaseid":"serbes-aldimashki-afastandaccuratechirprateestimationalgorithmbasedonthefractionalfouriertransform-2017","authorIDs":[],"author_short":["Serbes, A.","Aldimashki, O."],"bibdata":{"bibtype":"inproceedings","type":"inproceedings","author":[{"firstnames":["A."],"propositions":[],"lastnames":["Serbes"],"suffixes":[]},{"firstnames":["O."],"propositions":[],"lastnames":["Aldimashki"],"suffixes":[]}],"booktitle":"2017 25th European Signal Processing Conference (EUSIPCO)","title":"A fast and accurate chirp rate estimation algorithm based on the fractional Fourier transform","year":"2017","pages":"1105-1109","abstract":"In this work, a fast and accurate chirp-rate estimation algorithm is presented. The algorithm is based on the fractional Fourier transform. It is shown that utilization of the golden section search algorithm to find the maximum magnitude of the fractional Fourier transform domains not only accelerates the process, but also increases the accuracy in a noisy environment. Simulation results validate the proposed algorithm and show that the accuracy of parameter estimation nearly achieves the Cramer-Rao lower bound for SNR values as low as -7dB.","keywords":"chirp modulation;Fourier transforms;parameter estimation;search problems;fractional Fourier transform;golden section search algorithm;parameter estimation;chirp rate estimation algorithm;noise figure 7.0 dB;Chirp;Signal processing algorithms;Time-frequency analysis;Fourier transforms;Noise measurement;Signal to noise ratio;Chirp signals;fractional Fourier transform;chirp rate;golden section search","doi":"10.23919/EUSIPCO.2017.8081379","issn":"2076-1465","month":"Aug","url":"https://www.eurasip.org/proceedings/eusipco/eusipco2017/papers/1570342282.pdf","bibtex":"@InProceedings{8081379,\n author = {A. Serbes and O. Aldimashki},\n booktitle = {2017 25th European Signal Processing Conference (EUSIPCO)},\n title = {A fast and accurate chirp rate estimation algorithm based on the fractional Fourier transform},\n year = {2017},\n pages = {1105-1109},\n abstract = {In this work, a fast and accurate chirp-rate estimation algorithm is presented. The algorithm is based on the fractional Fourier transform. It is shown that utilization of the golden section search algorithm to find the maximum magnitude of the fractional Fourier transform domains not only accelerates the process, but also increases the accuracy in a noisy environment. Simulation results validate the proposed algorithm and show that the accuracy of parameter estimation nearly achieves the Cramer-Rao lower bound for SNR values as low as -7dB.},\n keywords = {chirp modulation;Fourier transforms;parameter estimation;search problems;fractional Fourier transform;golden section search algorithm;parameter estimation;chirp rate estimation algorithm;noise figure 7.0 dB;Chirp;Signal processing algorithms;Time-frequency analysis;Fourier transforms;Noise measurement;Signal to noise ratio;Chirp signals;fractional Fourier transform;chirp rate;golden section search},\n doi = {10.23919/EUSIPCO.2017.8081379},\n issn = {2076-1465},\n month = {Aug},\n url = {https://www.eurasip.org/proceedings/eusipco/eusipco2017/papers/1570342282.pdf},\n}\n\n","author_short":["Serbes, A.","Aldimashki, O."],"key":"8081379","id":"8081379","bibbaseid":"serbes-aldimashki-afastandaccuratechirprateestimationalgorithmbasedonthefractionalfouriertransform-2017","role":"author","urls":{"Paper":"https://www.eurasip.org/proceedings/eusipco/eusipco2017/papers/1570342282.pdf"},"keyword":["chirp modulation;Fourier transforms;parameter estimation;search problems;fractional Fourier transform;golden section search algorithm;parameter estimation;chirp rate estimation algorithm;noise figure 7.0 dB;Chirp;Signal processing algorithms;Time-frequency analysis;Fourier transforms;Noise measurement;Signal to noise ratio;Chirp signals;fractional Fourier transform;chirp rate;golden section search"],"metadata":{"authorlinks":{}},"downloads":0},"bibtype":"inproceedings","biburl":"https://raw.githubusercontent.com/Roznn/EUSIPCO/main/eusipco2017url.bib","creationDate":"2021-02-13T16:38:25.629Z","downloads":0,"keywords":["chirp modulation;fourier transforms;parameter estimation;search problems;fractional fourier transform;golden section search algorithm;parameter estimation;chirp rate estimation algorithm;noise figure 7.0 db;chirp;signal processing algorithms;time-frequency analysis;fourier transforms;noise measurement;signal to noise ratio;chirp signals;fractional fourier transform;chirp rate;golden section search"],"search_terms":["fast","accurate","chirp","rate","estimation","algorithm","based","fractional","fourier","transform","serbes","aldimashki"],"title":"A fast and accurate chirp rate estimation algorithm based on the fractional Fourier transform","year":2017,"dataSources":["2MNbFYjMYTD6z7ExY","uP2aT6Qs8sfZJ6s8b"]}