MIMO FMCW Radar-Based Indoor Mapping Through Exploiting Multipath Signals

This paper explores the application of a stationary multiple-input multiple-output frequency-modulated continuous-wave radar system for indoor environment mapping. In static situations, it’s challenging to create indoor maps using fixed radar systems because only a few strong reflection points are prominently visible in the detection results. Our proposed method uses a stationary radar system, leveraging multipath echoes of radar signals to produce detailed indoor maps. Ghost targets caused by multipath propagation of signals contain information about the geometry of propagation paths. Unlike existing studies that primarily aimed to mitigate ghost targets, our method uses the information provided by both real and ghost targets to improve the mapping of indoor environments. For this purpose, we first extract detected peaks in the range-azimuth domain and compare the estimated direction of arrival (DoA) and direction of departure (DoD) to identify ghost targets and real targets. Then, the positions of paired real and ghost targets are used to estimate the geometry of reflection points, aiding in the creation of maps for surrounding indoor environments. Finally, we use density based spatial clustering of applications with noise algorithm and running average filter and eliminate outliers, improving the accuracy and clarity of the generated indoor map. Simulation and experimentation results validate the effectiveness of the proposed method. The average RMSE of the estimated indoor map compared to the ground truth was 0.18 m.