Ling Huang
ABSTRACT
The study of Through Wall Radar Human Similar Behaviour Classification aims to classify and identify human behaviours through the use of Through Wall Radar technology. This study defines a metric for evaluating the network's ability to classify similar behaviours. In our experiments, we first collected a large amount of through-the-wall radar data and built a comprehensive and diverse database of human behaviours. Subsequently, we perform a simple data preprocessing on the data using MTI. Finally, we tested and evaluated the collected data with CNN, RNN, GRU, and LSTM. The results show that the metric can well evaluate the network's ability in classifying similarity data. In addition, we explored the similarities and differences between different human behaviours, analysed the similarities between such behaviours with different metrics, and added different similarity metrics to the network as regular terms for network training, and concluded that simple similarity metrics can often achieve good positive results.
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Index Terms
- Human similarity behaviour classification based on through-wall radar
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