.png){kind=icon}
返回
Data-Driven Radar Processing Using a Parametric Convolutional Neural Network for Human Activity Classification
.png){kind=icon}
OA
AI
DOI：10.1109/JSEN.2021.3092002.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
The paper proposes a data-driven pre-processing optimization for radar data using a parametric convolutional neural network. The proposed method is applied on human activity classification as a use case. Present radar-based activity recognition system exploit micro-Doppler signature by generating Doppler spectrograms or a temporal series of range-Doppler maps, followed by deep neural networks or machine learning approaches for classification. Those radar data representations are typically generated on the basis of short-time Fourier transformations. A Fourier transformation equally resolves the frequency space, which may be sub-optimal in some applications. Although deep convolutional neural networks (DCNN) have been shown to implicitly learn features from raw sensor data in other fields, such as speech recognition, yet, for the case of radar-based DCNNs, pre-processing is required to develop a scalable and robust classification or regression application. In this paper, we propose a parametric convolutional neural network that mimics the radar pre-processing across fast-time and slow-time radar data through 2D sinc filter or 2D wavelet filter kernels to extract features for classification of various human activities. During training only the filter parameters of the 2D sinc filters or 2D wavelets are learned, leading to optimized feature representation for the classification task. It is demonstrated that our proposed solution shows improved results compared to equivalent DCNN architectures that rely on Doppler spectrograms or radar data cubes as input data.
Keyword:
Radar
Doppler effect
Doppler radar
Sensors
Chirp
Feature extraction
Spectrogram
2D sinc filters
2D wavelets
parametric CNN
deep learning
human activity classification
期刊
IF:
4.5
论文数:
2.2W
被引数:
7.3W
机构
引用论文
.png){kind=icon}
1.84
μ
m
emission of Tm3+ sensitized by Yb3+ ions in monoclinic KGd(WO4)2 single crystals1.84 μm由Yb3+离子敏化的Tm3+在单斜KGd(WO4)2单晶中的发射
OAAI
OAAI分享收藏H plasma processing triggered phase transformation from DLC to diamond nano-particlesH等离子体处理触发了从DLC到金刚石纳米颗粒的相变。
PREAI
分享收藏
查看更多内容