Classifying Small Animals, Standing and Lying Down Humans With Multi-mmWave Radars

Millimeter-wave (mmWave) radar is a valuable technology for detecting and tracking beings and objects. Unlike cameras and light detection and ranging (LiDAR), it is robust against environmental factors like rain, dust, and fog. Additionally, it is noninvasive and preserves privacy, making it ideal for indoor applications. Its short wavelength enables high resolution with a compact antenna. However, detecting both people and small animals, crucial for applications like wireless energy transfer (WET) and fall detection, remains relatively unexplored. This challenge arises from differences in size and volume between targets, particularly when distinguishing a lying human from a small animal due to their similar height. To address this, we employ multiple radars, increasing classification accuracy from 65% with one radar to 90% with four radars. Leveraging combined radar data enhances target classification, reducing ghost targets and improving detection performance.