Grouped Target Tracking and Seamless People Counting with a 24 GHz MIMO FMCW

The problem of radar-based tracking of groups of people moving together and counting their numbers in indoor environments is considered here. A novel processing pipeline to track groups of people moving together and count their numbers is proposed and validated. The pipeline is specifically designed to deal with frequent changes of direction and stop & go movements typical of indoor activities. The proposed approach combines a tracker with a classifier to count the number of grouped people; this uses both spatial features extracted from range-azimuth maps, and Doppler frequency features extracted with wavelet decomposition. Thus, the pipeline outputs over time both the location and number of people present. The proposed approach is verified with experimental data collected with a 24 GHz Frequency Modulated Continuous Wave (FMCW) radar. It is shown that the proposed method achieves 95.59% accuracy in counting the number of people, and a tracking metric OSPA of 0.338. Furthermore, the performance is analyzed as a function of different relevant variables such as feature combinations and scenarios.

3D high-resolution imaging algorithm using 1D MIMO array for autonomous driving application

The problem of 3D high-resolution imaging in automotive multiple-input multiple-output (MIMO) side-looking radar using a 1D array is considered. The concept of motion-enhanced snapshots is introduced for generating larger apertures in the azimuth dimension. For the first time, 3D imaging capabilities can be achieved with high angular resolution using a 1D MIMO antenna array, which can alleviate the requirement for large radar systems in autonomous vehicles. The robustness to variations in the vehicle's movement trajectory is also considered and addressed with relevant compensations in the steering vector. The available degrees of freedom as well as the Signal to Noise Ratio (SNR) are shown to increase with the proposed method compared to conventional imaging approaches. The performance of the algorithm has been studied in simulations, and validated with experimental data collected in a realistic driving scenario.