Tracking and Identification of Targets via mmWave MIMO Radar

摘要

Sensing is essential to enable civil, industrial, and military applications that require situational awareness. Simultaneous tracking and identification of heterogeneous device-free targets (e.g., humans, robots, and vehicles) can provide information superiority for different types of operations and surveillance tasks. This paper presents a framework for tracking and identification of multiple device-free targets based on reflected radiofrequency signals. The proposed framework consists of (i) clutter mitigation and target detection relying on the estimated clutter intensity distribution in the environment; (ii) multitarget tracking relying on probabilistic data association; and (iii) neural network-based classification for target identification relying on time-domain representations of micro–Doppler signatures generated by target movements. We performed an experimentation, employing an frequency modulated continuous wave multiple-input–multiple-output radar at mmWaves, which validates the proposed framework. The experimental results, in terms of tracking and identification accuracies, show the benefits of using the proposed framework.