Embedded Micro Radar for Pedestrian Detection in Clutter

Embedded micro radars that include integrated hardware, application software, and a real-time operating system as part of an enclosed system provide convenient platforms for outdoor and indoor environment monitoring. This paper discusses methods to suppress clutter and to extract features of weak radar targets, such as pedestrians. With the help of MATLAB® simulation tools, algorithms to detect pedestrians in a high clutter environment can be investigated. A hybrid neural network is developed on micro-Doppler signatures generated synthetically. It outperforms the traditional convolutional neural network in terms of accuracy and the amount of training data required. We then use an embedded micro radar for field trials to test the performance of the hybrid neural network on real data sets.