Human and Small Animal Detection Using Multiple Millimeter-Wave Radars and Data Fusion: Enabling Safe Applications

Area of Science:

• Sensor Technology
• Robotics and Automation
• Biomedical Engineering

Background:

• Millimeter-wave (mmWave) radars offer high resolution and privacy preservation, unaffected by environmental conditions.
• Simultaneous detection of people and small animals is crucial for applications like indoor wireless energy transfer.
• Challenges include varying target sizes and volumes, necessitating advanced detection methodologies.

Purpose of the Study:

• To explore challenges in using mmWave radars for simultaneous detection of humans and small animals.
• To propose innovative methods for enhancing detection accuracy in indoor environments.
• To evaluate the effectiveness of data-fusion techniques with multiple mmWave radars.

Main Methods:

• Utilized up to four mmWave radars in two distinct indoor positioning scenarios.
• Investigated the detection and tracking of both humans and small animals.
• Compared the performance of three different data-fusion methods.

Main Results:

• Single radar without tracking yielded 46.1% sensitivity.
• Optimal fusion method with four radars and tracking achieved 97.10% sensitivity.
• Demonstrated significant improvement in detection sensitivity and reliability.

Conclusions:

• Multiple mmWave radars combined with data fusion and tracking substantially enhance target detection.
• The proposed methodologies effectively overcome challenges in detecting diverse targets.
• This approach significantly improves sensitivity and reliability for indoor monitoring applications.