Evaluation of different super-resolution techniques for automotive applications

This work presents results of the application of different super-resolution techniques to real world scenarios. The sensor used for the measurements utilizes a synthetic aperture with two independent transmit elements. For better exploitation of the given aperture super-resolution techniques are used, namely linear prediction, ESPRIT, MUSIC and Root-MUSIC. These algorithms are compared in simulation with respect to their ability to separate targets and their computational effort. Finally measurement results from scenarios using corner reflectors and real life environment are presented.