| 许志猛,张钐钐,陈良琴,孙北晨.基于时空域增强微多普勒谱图的行为识别方法[J].电子测量与仪器学报,2022,36(7):144-151 |
| 基于时空域增强微多普勒谱图的行为识别方法 |
| Behavior recognition based on spatiotemporalenhanced micro-Doppler spectrogram |
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| DOI： |
| 中文关键词: FMCW 雷达 智能监护 增强微多普勒特征 ConvLSTM 网络 |
| 英文关键词:FMCW radar intelligent monitoring enhanced micro-Doppler feature ConvLSTM network |
| 基金项目:国家自然科学基金（62071125）、福建省产学研合作项目（2019H6007）、福建省自然科学基金（2021J01581，2018J01805）、福州大学科研基金（GXRC 18083）项目资助 |
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| 中文摘要: |
| 为缓解新冠疫情下医护人员短缺的现象,实现对住院患者的智能监护,本文基于调频连续波(FMCW)雷达提出了一种
新的基于时空域增强微多普勒谱图的行为识别方法。 首先,该方法对雷达获取的人体行为数据构造微多普勒谱图;然后利用一
种新的直方图均衡化和同态滤波相结合的时空域增强算法用于谱图信息的增强;最后采用一种改进的卷积长短时记忆网络
(ConvLSTM)提取谱图的时空域特征,并有效辨识喝水、跌倒等 7 种住院患者常见行为。 实验结果表明,基于本文方法对 7 种动
作的识别准确率能达到 94%,可以有效的监护患者的行为。 |
| 英文摘要: |
| To alleviate the shortage of health care workers under the novel coronavirus pneumonia (COVID-19) and to achieve intelligent
monitoring of inpatients, this paper proposes a new behavior recognition method based on enhanced micro-Doppler spectrograms in the
space-time domain using frequency modulated continuous wave (FMCW) radar. Firstly, constructing a micro-Doppler spectrum of the
human behavior acquired by the radar. Then, a new time-space domain enhancement algorithm combining histogram equalization and
homomorphic filtering is used for the enhancement of spectrogram information. Finally, an improved convolutional long short term
memory network (ConvLSTM) is proposed to extract the time and space features of the spectrum, which effectively identifies seven
common inpatient behaviors, such as drinking and falling. The experimental results show that the method in this paper can effectively
monitor the patient's behavior, and the recognition accuracy of the seven actions can reach 94%. |
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