Radar-Based Human Activity Recognition Under the Limited Measurement Data Support Using Domain Translation

In recent years, radar-based human activity recognition has received considerable interest, but it faces the difficulty of a shortage of training data. In this research, a two-stage domain adaption method is proposed for this issue. This method combines simulated radar spectrograms with an elaborated domain-translation network to perform domain adaptation, hence enabling human activity recognition with limited measurement data support. To validate the efficacy of our method, we conduct radar simulation and measurements, and the experimental results demonstrate that the proposed method outperforms other comparisons in terms of accuracy, showing its great capacity for radar-based human activity recognition.