The problem of detection and localization of multiple people using a network of Ultra-Wide Band (UWB) radar nodes in the cabin of a vehicle is addressed in this paper. Specifically, an algorithm for decentralized vital signs detection is proposed, based on the analysis of a novel model for radar signatures of vital signs. Additionally, a centralized association processing block is used to fuse the detections from all radars in the network using a dedicated cost-matrix computation. The performance of the proposed processing pipeline is tested experimentally with a multistatic radar network, and a simulation framework is also developed to evaluate the performance in alternative topologies of the radar network beyond the experiments. It is shown that the detection and localization of humans within the car environment is possible with the proposed processing pipeline, with localization Root Mean Square Error.

A numerical model is developed in the electromagnetic software suite FEKO to simulate scattering from surfaces with pre-defined statistical properties. The model considers surface roughness profile, incident angle and source polarization. Statistical analysis of the scattered field is performed using the Monte Carlo method using full-wave scattering results from a statistical ensemble of rough surface realizations. The performance of the numerical model has been verified in the limiting case of small height and small slope surfaces by comparison with the small perturbation theory. By means of the model proposed, new insight in scattering from statistical surfaces with an averaged surface slope above 0,5 as well as non-Gaussian surface statistics has been obtained.