An efficient target detection algorithm via Karhunen‐Loève transform for frequency modulated continuous wave (FMCW) radar applications
Abstract This paper investigates an advanced effective signal processing technique to suppress noise, addressing a modern high‐performance detection in the field of radar sensing. To achieve a higher accuracy, the frequency modulated continuous wave radar is taken as a case study to derive the algor...
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| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2022-09-01
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| Series: | IET Signal Processing |
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| Online Access: | https://doi.org/10.1049/sil2.12111 |
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| _version_ | 1832559601955897344 |
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| author | Luoyan Zhu Yinsheng Liu Danping He Ke Guan Bo Ai Zhangdui Zhong Xi Liao |
| author_facet | Luoyan Zhu Yinsheng Liu Danping He Ke Guan Bo Ai Zhangdui Zhong Xi Liao |
| author_sort | Luoyan Zhu |
| collection | DOAJ |
| description | Abstract This paper investigates an advanced effective signal processing technique to suppress noise, addressing a modern high‐performance detection in the field of radar sensing. To achieve a higher accuracy, the frequency modulated continuous wave radar is taken as a case study to derive the algorithm based on Karhunen ‐ Loève transform (KLT) before detection. KLT defines a linear projection of the signal statistics on the eigenfunctions domain, which makes the input‐dependent signals orthogonal to each other under new eigen‐basis and eigenvalues. The highest energy along slow time dimension of each range bin is concentrated in the transformed domain corresponding to the largest N eigenvalues. The performance of the algorithm is evaluated by different eigenvalue selection strategies. Numerical experiments are employed to obtain the relationship between signal‐to‐noise ratio and different eigenvalue selection strategies. Pertaining to the detection performance, constant false alarm ratio detector is applied to demonstrate the detection ability as a result of the processor by use of probability of detection (Pd). |
| format | Article |
| id | doaj-art-0a3bd844e6414afd86793dd8790b54d4 |
| institution | Kabale University |
| issn | 1751-9675 1751-9683 |
| language | English |
| publishDate | 2022-09-01 |
| publisher | Wiley |
| record_format | Article |
| series | IET Signal Processing |
| spelling | doaj-art-0a3bd844e6414afd86793dd8790b54d42025-02-03T01:29:37ZengWileyIET Signal Processing1751-96751751-96832022-09-0116780081010.1049/sil2.12111An efficient target detection algorithm via Karhunen‐Loève transform for frequency modulated continuous wave (FMCW) radar applicationsLuoyan Zhu0Yinsheng Liu1Danping He2Ke Guan3Bo Ai4Zhangdui Zhong5Xi Liao6State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Beijing ChinaState Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Beijing ChinaState Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Beijing ChinaState Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Beijing ChinaState Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Beijing ChinaState Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Beijing ChinaThe Chongqing Key Laboratory of Complex Environmental Communications School of Communication and Information Engineering Chongqing University of Posts and Telecommunications Chongqing ChinaAbstract This paper investigates an advanced effective signal processing technique to suppress noise, addressing a modern high‐performance detection in the field of radar sensing. To achieve a higher accuracy, the frequency modulated continuous wave radar is taken as a case study to derive the algorithm based on Karhunen ‐ Loève transform (KLT) before detection. KLT defines a linear projection of the signal statistics on the eigenfunctions domain, which makes the input‐dependent signals orthogonal to each other under new eigen‐basis and eigenvalues. The highest energy along slow time dimension of each range bin is concentrated in the transformed domain corresponding to the largest N eigenvalues. The performance of the algorithm is evaluated by different eigenvalue selection strategies. Numerical experiments are employed to obtain the relationship between signal‐to‐noise ratio and different eigenvalue selection strategies. Pertaining to the detection performance, constant false alarm ratio detector is applied to demonstrate the detection ability as a result of the processor by use of probability of detection (Pd).https://doi.org/10.1049/sil2.12111radar detectionradar signal processing |
| spellingShingle | Luoyan Zhu Yinsheng Liu Danping He Ke Guan Bo Ai Zhangdui Zhong Xi Liao An efficient target detection algorithm via Karhunen‐Loève transform for frequency modulated continuous wave (FMCW) radar applications IET Signal Processing radar detection radar signal processing |
| title | An efficient target detection algorithm via Karhunen‐Loève transform for frequency modulated continuous wave (FMCW) radar applications |
| title_full | An efficient target detection algorithm via Karhunen‐Loève transform for frequency modulated continuous wave (FMCW) radar applications |
| title_fullStr | An efficient target detection algorithm via Karhunen‐Loève transform for frequency modulated continuous wave (FMCW) radar applications |
| title_full_unstemmed | An efficient target detection algorithm via Karhunen‐Loève transform for frequency modulated continuous wave (FMCW) radar applications |
| title_short | An efficient target detection algorithm via Karhunen‐Loève transform for frequency modulated continuous wave (FMCW) radar applications |
| title_sort | efficient target detection algorithm via karhunen loeve transform for frequency modulated continuous wave fmcw radar applications |
| topic | radar detection radar signal processing |
| url | https://doi.org/10.1049/sil2.12111 |
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