IEEE Open Journal of Signal Processing (Jan 2023)
Joint Localization and Environment Sensing of Rigid Body With 5G Millimeter Wave MIMO
Abstract
Accurately localizing a target in three-dimensional (3D) space assisted with the fifth generation (5G) wireless systems in an indoor environment could enable a wide variety of new applications, including precise control for factory automation, self-maneuver of the vehicle and so on. However, controlling a target in 3D space relies on a rigid body modelling with six degrees of freedom, which dramatically increases the localization difficulty and complexity. Furthermore, for radio-based localization methods, the lack of line-of-sight (LOS) and the existence of reflection points in the environment will also influence the rigid body localization process. To improve the rigid body localization accuracy as well as unravel useful environmental information from the received signal, a novel rigid body joint active localization and environment sensing scheme is proposed in this article. Specifically, the multi-path effect of millimeter wave (mm-wave) signal with a single reflection can be exploited to enhance the rigid body localization accuracy, and it can also be utilized to locate the reflection points, which further enables a new way for environmental sensing. Hence, we first propose a two-step hierarchical compressive sensing algorithm to extract the angular and distance information of the LOS (if available) and single-bounce specular reflections. Then a particle swarm optimization (PSO) based method is derived to recover the posture of the rigid body and the location of reflection points. The Cramér-Rao lower bound (CRLB) on angle, rigid body posture and reflection points position uncertainty is also analyzed. The simulation results demonstrate that the proposed scheme can achieve high accuracy rigid body localization and locate the reflection points around the rigid body even under obstructed-line-of-sight (OLOS) conditions in an indoor scene.
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