Development and Testing of a Low Cost Audio Based ISAR Imaging and Machine Learning System for Radar Education

Abstract

This paper describes the development and testing of low cost Inverse Synthetic Aperture Radar (ISAR) turn table system with a machine learning back-end. The ISAR sensor is based on audio components which mimic the functioning of a radar system but at a much lower cost. The system is also compact enough to fit on a single desk for classroom demonstrations and experiments. The system can record range lines as the turn table revolves and form ISAR images. These images can then be used to train machine learning algorithms to demonstrate the accuracy of such algorithms. The system thus allows for classroom demonstrations of the sensor to classifier chain in a way that is immediately accessible to students.