An Adaptive Filtering Algorithm Based on Range-Doppler Information Guidance
Millimetre-wave frequency-modulated continuous-wave (FMCW) radar is widely used in various scenarios. However, it is often affected by static and dynamic clutter interference, which has a negative impact on its performance. Specifically, these clutter signals are often mistaken for target signals, l...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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IEEE
2023-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10365169/ |
| _version_ | 1797372199045169152 |
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| author | Zhuo Li Jun Zhang Biyuan Li Jiazhi Yu |
| author_facet | Zhuo Li Jun Zhang Biyuan Li Jiazhi Yu |
| author_sort | Zhuo Li |
| collection | DOAJ |
| description | Millimetre-wave frequency-modulated continuous-wave (FMCW) radar is widely used in various scenarios. However, it is often affected by static and dynamic clutter interference, which has a negative impact on its performance. Specifically, these clutter signals are often mistaken for target signals, leading to false detection and affecting the accuracy of target tracking and localization. In addition, dynamic clutter sources, such as other moving objects, also bring about Doppler frequency shift interference, further affecting the measurement of target velocity. In this paper, addressing the issue of static clutter, we propose a frame mean subtraction method. Additionally, for the more complex problem of dynamic clutter, we introduce a filtering approach guided by distance-Doppler information. This method utilizes a mask generated in real-time by tracking the temporal distance information of the target as prior information for filtering radar signals. Subsequently, we employ a novel fractional short-time Fourier transform to extract the Doppler feature spectrogram of the radar signal. Finally, a ResNet-50 model trained on the Doppler spectrograms of interference-free radar signals is used to test the Doppler maps generated from the filtered radar signals. After testing, the classification accuracy reaches 97.5%. This result shows that the micro-Doppler spectrum obtained by filtering the radar signal collected in complex scenes using the proposed method is highly similar to the micro-Doppler spectrum of the target to be measured. In addition, the proposed filtering method not only plays the role of signal filtering, but also enhances the strength of the target signal and provides more detailed information for the subsequent recognition task. |
| first_indexed | 2024-03-08T18:31:27Z |
| format | Article |
| id | doaj.art-1789e8532466412da605a7bb7f694fb7 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-03-08T18:31:27Z |
| publishDate | 2023-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-1789e8532466412da605a7bb7f694fb72023-12-30T00:04:04ZengIEEEIEEE Access2169-35362023-01-011114566114567810.1109/ACCESS.2023.334463110365169An Adaptive Filtering Algorithm Based on Range-Doppler Information GuidanceZhuo Li0https://orcid.org/0009-0002-1621-7266Jun Zhang1Biyuan Li2https://orcid.org/0000-0002-1361-1404Jiazhi Yu3https://orcid.org/0000-0002-9220-8989School of Electronic Engineering, Tianjin University of Technology and Education, Tianjin, ChinaSchool of Electronic Engineering, Tianjin University of Technology and Education, Tianjin, ChinaSchool of Electronic Engineering, Tianjin University of Technology and Education, Tianjin, ChinaSchool of Electronic Engineering, Tianjin University of Technology and Education, Tianjin, ChinaMillimetre-wave frequency-modulated continuous-wave (FMCW) radar is widely used in various scenarios. However, it is often affected by static and dynamic clutter interference, which has a negative impact on its performance. Specifically, these clutter signals are often mistaken for target signals, leading to false detection and affecting the accuracy of target tracking and localization. In addition, dynamic clutter sources, such as other moving objects, also bring about Doppler frequency shift interference, further affecting the measurement of target velocity. In this paper, addressing the issue of static clutter, we propose a frame mean subtraction method. Additionally, for the more complex problem of dynamic clutter, we introduce a filtering approach guided by distance-Doppler information. This method utilizes a mask generated in real-time by tracking the temporal distance information of the target as prior information for filtering radar signals. Subsequently, we employ a novel fractional short-time Fourier transform to extract the Doppler feature spectrogram of the radar signal. Finally, a ResNet-50 model trained on the Doppler spectrograms of interference-free radar signals is used to test the Doppler maps generated from the filtered radar signals. After testing, the classification accuracy reaches 97.5%. This result shows that the micro-Doppler spectrum obtained by filtering the radar signal collected in complex scenes using the proposed method is highly similar to the micro-Doppler spectrum of the target to be measured. In addition, the proposed filtering method not only plays the role of signal filtering, but also enhances the strength of the target signal and provides more detailed information for the subsequent recognition task.https://ieeexplore.ieee.org/document/10365169/LFMCWmicro-dopplerradar signal filteringconvolutional neural network |
| spellingShingle | Zhuo Li Jun Zhang Biyuan Li Jiazhi Yu An Adaptive Filtering Algorithm Based on Range-Doppler Information Guidance IEEE Access LFMCW micro-doppler radar signal filtering convolutional neural network |
| title | An Adaptive Filtering Algorithm Based on Range-Doppler Information Guidance |
| title_full | An Adaptive Filtering Algorithm Based on Range-Doppler Information Guidance |
| title_fullStr | An Adaptive Filtering Algorithm Based on Range-Doppler Information Guidance |
| title_full_unstemmed | An Adaptive Filtering Algorithm Based on Range-Doppler Information Guidance |
| title_short | An Adaptive Filtering Algorithm Based on Range-Doppler Information Guidance |
| title_sort | adaptive filtering algorithm based on range doppler information guidance |
| topic | LFMCW micro-doppler radar signal filtering convolutional neural network |
| url | https://ieeexplore.ieee.org/document/10365169/ |
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