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Radar-Based Human Activity Recognition Using Hybrid Neural Network Model With Multidomain Fusion.
- Source :
-
IEEE Transactions on Aerospace & Electronic Systems . Oct2021, Vol. 57 Issue 5, p2889-2898. 10p. - Publication Year :
- 2021
-
Abstract
- This article concerns the issue of how to combine the multidomainradar information, including range–Doppler, time–Doppler, and time–range, for human activity recognition. Specifically, to fully make use of radar information, instead of using a single-domain spectrum as inputs, a novel hybrid neural network model is developed for exploring multidomain fusion of radar information. In doing this, three kinds of 2-D domain spectra are used in a fashion of supplementing each other with a hybrid framework that combines three models: 1-D convolution neural network, recurrent neural network, and 2-D convolution network. It is advantageous to use such a hybrid model to capture much rich features through multidomain feature fusion, so as to improve the accuracy of human activity recognition effectively. Experimental results validate the proposed method. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 00189251
- Volume :
- 57
- Issue :
- 5
- Database :
- Academic Search Index
- Journal :
- IEEE Transactions on Aerospace & Electronic Systems
- Publication Type :
- Academic Journal
- Accession number :
- 153732982
- Full Text :
- https://doi.org/10.1109/TAES.2021.3068436