Device-free indoor localization and tracking using commercial millimeter wave radars have attracted much interest lately due to their non-intrusive nature and high spatial resolution. However, it is challenging to achieve high tracking accuracy due to rich multipath reflection and occlusion in indoor environments. Static objects with non-negligible reflectance of mmWave signals interact with moving human subjects and generate time-varying multipath ghosts and shadow ghosts, which can be easily confused as real subjects. To characterize the complex interactions, we first develop a geometric model that estimates the location of multipath ghosts given the locations of humans and static reflectors. Based on this model, the locations of static reflectors that form a reflection map are automatically estimated from received radar signals as a single person traverses the environment along arbitrary trajectories. The reflection map allows for the elimination of multipath and shadow ghost interference as well as the augmentation of weakly reflected human subjects in occluded areas. The proposed environment-aware multi-person tracking system can generate reflection maps with a mean error of 15.5cm and a 90-percentile error of 30.3cm, and achieve multi-person tracking accuracy with a mean error of 8.6cm and a 90-percentile error of 17.5cm, in four representative indoor spaces with diverse subjects using a single mmWave radar.