Remote detection of humans and animals

Abstract

Detecting humans and distinguishing them from natural fauna is an important issue in border security applications. In particular, it is important to detect and classify people who are walking in remote locations and transmit back detections over extended periods at a low cost and with minimal maintenance. Our simulation and measurement work has been relatively successful in providing a qualitative guide to improving our analysis, and has produced a reasonable model for studying signatures using radar micro-Doppler. This paper presents data on humans and animals at multiple angles and directions of motion, as well as features that can be extracted from radar data for the classification as animal versus human.