  Millimeter-wave (mmWave) systems in the 30--300 GHz bands are among the
fundamental enabling technologies of 5G and beyond 5G, providing large
bandwidths, not only for high data rate communication, but also for precise
positioning services, in support of high accuracy demanding applications such
as vehicle positioning. With the possibility to introduce relatively large
arrays on user devices with a small footprint, the ability to determine the
user orientation becomes unlocked. The estimation of the full user pose (joint
3D position and 3D orientation) is referred to as 6D localization.
Conventionally, the problem of 6D localization using antenna arrays has been
considered difficult and was solved through a combination of heuristics and
optimization. In this paper, we reveal a close connection between the AoA and
AoD and the well-studied perspective projection model from computer vision.
This connection allows us to solve the 6D localization problem, by adapting
state-of-the-art methods from computer vision. More specifically, two problems,
namely 6D pose estimation from AoA from multiple single-antenna base stations
and 6D SLAM based on single-BS mmWave communication, are first modeled with the
perspective projection model, and then solved. Numerical simulations show that
the proposed estimators operate close to the theoretical performance bounds.
Moreover, the proposed SLAM method is effective even in the absence of the LoS
path, or knowledge of the LoS/NLoS condition.
