Simultaneous Position and Orientation Estimation for Visible Light Systems With Multiple LEDs and Multiple PDs

Shen, Shengqiang; Li, Shiyin; Steendam, Heidi

doi:10.1109/jsac.2020.3000805

Cited by 46 publications

(19 citation statements)

References 70 publications

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“…In contrast, in 3D a single BS does not suffice to determine the UE orientation, since only angles in azimuth and elevation can be measured, unless additional signal sources are available, e.g., reflectors or scatterers [3], reconfigurable intelligent surfaces [12], or additional BSs. Joint localization and orientation estimation was also considered in [13], for anchor-free swarm navigation system, in [14] for visible light positioning, in [15] for realistic channel realizations with hybrid array architectures, and in [16] for relative localization of vehicles. Orientation estimation from range measurements is also possible, as described in [17].…”

Section: Introductionmentioning

confidence: 99%

3D Orientation Estimation with Multiple 5G mmWave Base Stations

Nazari

Seco‐Granados

Johannisson

et al. 2021

ICC 2021 - IEEE International Conference on Communications

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We consider the problem of estimating the 3D orientation of a user, using the downlink mmWave signals received from multiple base stations. We show that the received signals from several base stations, having known positions, can be used to estimate the unknown orientation of the user. We formulate the estimation problem as a maximum likelihood estimation problem in the the manifold of rotation matrices. In order to provide an initial estimate to solve the non-linear non-convex optimization problem, we resort to a least squares estimation problem that exploits the underlying geometry. Our numerical results show that the problem of orientation estimation can be solved when the signals from at least two base stations are received. We also provide the orientation lower error bound, showing a narrow gap between the performance of the proposed estimators and the bound.

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Section: Introductionmentioning

confidence: 99%

3D Orientation Estimation with Multiple 5G mmWave Base Stations

Nazari

Seco‐Granados

Johannisson

et al. 2021

ICC 2021 - IEEE International Conference on Communications

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“…As the solution of the above (iterative) constrained optimization problem is complex and cumbersome in Euclidean space, we first notice that

is a manifold and convert the above optimization problem into an unconstrained optimization problem on manifolds [ 26 ]. In what follows, we use the Gauss–Newton method on manifold

to solve ( 26 ), similarly as in [ 27 ]. At each iteration, the update direction is calculated by

where

is the Moore–Penrose pseudoinverse, and

the gradient of

with respect to

.…”

Section: Calibration and Pose Estimationmentioning

confidence: 99%

Pose Estimation for Visible Light Systems Using a Quadrature Angular Diversity Aperture Receiver

Shen

Sánchez

et al. 2022

Sensors

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The quadrature angular diversity aperture (QADA) receiver, consisting of a quadrant photodiode (QPD) and an aperture placed above the QPD, has been investigated for pose estimation for visible light systems. Current work on pose estimation for the QADA receiver uses classical camera sensor algorithms well known in computer vision. To this end, however, the light spot center first has to be obtained based on the RSS. However, this is less straightforward than for camera sensors, as in contrast to such sensors where the relationships are linear, the RSS output from the QADA is a non-linear function of the light spot position. When applying closed form solutions or iterative methods for cameras on a QADA, the non-linearity will degrade their performance. Furthermore, since in practice the aperture is not always perfectly aligned with the QPD, a procedure to calibrate the receiver is needed. Current work on calibration requires additional sophisticated equipment to measure the pose during calibration, which increases the difficulty of implementation. In this paper, we target the above problems for pose estimation and calibration of the QADA receiver. To this end, we first study the effect of the strategy of differencing and normalization on the probability density function (PDF), a commonly applied strategy for the QPD’s robustness against RSS variation, and it is shown that the applied strategy results in a complex PDF, which makes an effective and efficient estimation hard to achieve. Therefore, we derive an approximated PDF in a simple closed-form, based on which the calibration and the pose estimation algorithms using the least squares principle are proposed. The proposed calibration does not require any information about the pose of the receiver and is robust to variation of the received power and imperfect knowledge of the radiation pattern of the LED, making it easy to implement. We also derive the corresponding Cramér-Rao lower bound on the misalignment to benchmark the performance of the misalignment and to serve as an indicator to determine the required signal-to-noise ratio (SNR) or number of LEDs to obtain a desired accuracy. The calibration and pose estimation are evaluated by means of a Monte Carlo simulation. Computer simulations show that this theoretical bound is close to the RMSE of the proposed estimator and that the proposed pose estimator outperforms the PnP algorithm.

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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%

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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Simultaneous Position and Orientation Estimation for Visible Light Systems With Multiple LEDs and Multiple PDs

Cited by 46 publications

References 70 publications

3D Orientation Estimation with Multiple 5G mmWave Base Stations

3D Orientation Estimation with Multiple 5G mmWave Base Stations

Pose Estimation for Visible Light Systems Using a Quadrature Angular Diversity Aperture Receiver

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

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