An Investigation and Solution of Angle Based Rigid Body Localization

Wang, Yue; Wang, Gang; Chen, Shanjie; Ho, K. C.

doi:10.1109/tsp.2020.3022001

Cited by 21 publications

(5 citation statements)

References 53 publications

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“…Albeit there have been many investigations into real-time localization for many years, this area is attracting growing research interest due to new harsh localization environments and stringent accuracy requirements from many emerging applications. Traditionally, a target is modelled as a point target whose location is only defined by the 3D coordinates with three degrees of freedom while neglecting its orientations [2]. However, to achieve accurate maneuvering for tasks like B. Li and X. Wang are with the Department of Electrical and Computer Engineering, Western University, London, ON N6A 5B9, Canada.…”

Section: Introductionmentioning

confidence: 99%

Joint Localization and Environment Sensing of Rigid Body With 5G Millimeter Wave MIMO

Wang

et al. 2023

IEEE Open J. Signal Process.

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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 paper. 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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Section: Introductionmentioning

confidence: 99%

Joint Localization and Environment Sensing of Rigid Body With 5G Millimeter Wave MIMO

Wang

et al. 2023

IEEE Open J. Signal Process.

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“…In recent years, driven by diverse user demands and the rapid advancements in AI technology, an increasing number of smart devices, including robots, robotic arms, space vehicles, and various rigid bodies, have found extensive application in areas such as unknown area exploration, smart factory manufacturing, and outer space exploration. To guarantee the application of the above devices for high precision and real-time update of their status information, it is most important to accurately acquire the position parameters and the orientation information or motion direction [7], [8]. For instance, in industrial manufacturing, motion direction information is pivotal in determining the orientation of robot arms and other equipment, thus ensuring efficient and accurate industrial production.…”

Section: Introductionmentioning

confidence: 99%

Joint Rigid Body Localization and Wireless Signal Transmission Parameter Estimation Under NLOS Environment

Wan,

Li,

Wei

et al. 2023

IEEE Access

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To improve the performance of the rigid body localization (RBL) in the non-line-of-sight (NLOS) environment, this paper delves into a joint estimation method about the wireless signal transmission parameter and the attitude parameters of the rigid body,employing Time Difference of Arrival (TDOA) and Received Signal Strength (RSS) measurements. In the initial phase, the rigid body sensors localization problem is transformed into a difference of convex (DC) programming based on the TDOA measurement, and the concave-convex procedure (CCCP) is adopted to solve the initial estimate of the rigid body sensors position. Subsequently, the positions of the rigid body sensors are estimated based on the RSS measurement, and the wireless signal transmission parameters are obtained by using the weighted least square method. Finally, the minimization objective function is reconstructed is reconstructed by incorporating modified RSS and TDOA measurements. The attitude parameters of the rigid body are then determined using a combination of the bisection method and singular value decomposition (SVD). Simulation results demonstrate the effectiveness of this proposed approach in significantly enhancing RBL accuracy under NLOS environments.INDEX TERMS Rigid body localization, non-line-of-sight, difference of convex programming, concave-convex procedure.

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“…The 6D localization problem was introduced in the mmWave context in [30], but has not yet been further developed. However, it has been studied in other settings, e.g., visible light positioning (VLP) [31] and rigid body localization (RBL) [32]- [34], and of course in robotics [5]. In [31], a simultaneous 3D position and 3D orientation estimation using the received signal strength (RSS) for a visible light system containing multiple LEDs and multiple photodiodes is considered, and an approximate solution using direct linear transformation method is proposed.…”

Section: Introductionmentioning

confidence: 99%

“…This solution is further refined using iterative algorithms for ML estimation. On a parallel track, the problem is addressed under the label of RBL in [32]- [34]. Their approach is to mount sensors with a known topology on the body.…”

Section: Introductionmentioning

confidence: 99%

MmWave 6D Radio Localization with a Snapshot Observation from a Single BS

Nazari¹,

Seco‐Granados²,

Johannisson³

et al. 2022

Preprint

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Accurate and ubiquitous localization is crucial for a variety of applications such as logistics, navigation, intelligent transport, monitoring, and control. Exploiting mmWave signals in 5G and Beyond 5G systems can provide accurate localization with limited infrastructure. We consider the single base station localization problem and extend it to 3D position and 3D orientation estimation of an unsynchronized multi-antenna user, using downlink MIMO-OFDM signals. Through a Fisher information analysis, we show that the problem is often identifiable, provided that there is at least one additional multipath component, even if the position of corresponding incidence point is a priori unknown. Subsequently, we pose a maximum likelihood (ML) estimation problem, to jointly estimate the 3D position and 3D orientation of the user as well as several nuisance parameters (the user clock offset and the positions of incidence points corresponding to the multipath). The ML problem is a highdimensional non-convex optimization problem over a product of Euclidean and Riemannian manifolds. To avoid complex exhaustive search procedures, we propose a geometric initial estimate of all parameters, which reduces the problem to a 1dimensional search over a finite interval. Numerical results show the efficiency of the proposed ad-hoc estimation, whose gap to the Cramér-Rao bound (CRB) is tightened using ML estimation.

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An Investigation and Solution of Angle Based Rigid Body Localization

Cited by 21 publications

References 53 publications

Joint Localization and Environment Sensing of Rigid Body With 5G Millimeter Wave MIMO

Joint Localization and Environment Sensing of Rigid Body With 5G Millimeter Wave MIMO

Joint Rigid Body Localization and Wireless Signal Transmission Parameter Estimation Under NLOS Environment

MmWave 6D Radio Localization with a Snapshot Observation from a Single BS

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