Three-dimensional Localization Research Articles

Study of dynamics-microphysical-lightning activity characteristics in a tropical hailstorm

Based on three-dimensional lightning locations and S-band polarimetric Doppler radar data, a hailstorm that occurred on Hainan Island on June 4, 2021 was analyzed in detail. The analysis revealed that the flash activity of hailstorms is mainly intracloud (IC) flashes, the cloud-to-ground (CG) flashes frequency were less, positive CG flashes (+CG) were domination in the CG activity before hailfall. The flash frequency appeared “lightning jumps” when hailstorms merging with convective cells, ice hydrometeors also rapidly increased in the clouds of the mixed-phase area in this period, which was beneficial for efficient electrification. The Zdr column and evolution of echo top indicated presence of an intense updraft during the mature stage of the hailstorm. Zdr column depth about 4 km close to 20 °C during the mature stage. Near the time of the hailfall, Zdr column was contraction, due to sinking hail generated downdraft within the cloud. Zdr column after hailfall may be produced by the convergence of downdraft and sea breeze. In combination with the spatiotemporal distribution of the hydrometeors in hailstorms, flash activity was most closely related to graupel and it plays a important role for flashes electrification. The hail plays a minimum role in charge separation. Radiation sources were concentrated between 50 dBZ and 55 dBZ. The spatial distribution of radiation sources indicated possible complex charge structure within hail storm clouds.

Three-dimensional acoustic emission source localization method for layered rock considering anisotropic P-wave velocity

Three-dimensional acoustic emission source localization method for layered rock considering anisotropic P-wave velocity

Dressed state analysis of two- and three-dimensional atom localization in the $$\Lambda -\Xi$$ configuration

Dressed state analysis of two- and three-dimensional atom localization in the $$\Lambda -\Xi$$ configuration

Three-Dimensional Signal Source Localization with Angle-Only Measurements in Passive Sensor Networks

Some passive sensors can provide only relative angles of a signal source. To obtain the signal source location, multiple passive sensors can be constructed into a passive sensor network through communication links. This paper investigates the source localization problem with angle-only measurements in three-dimensional space. First, we present an intersection localization method, which estimates the target position by minimizing the sum of distances between lines formed by angle-only measurements. It has the same target position estimate as the widely used least-squares (LS) method, but with a lower computational cost. Furthermore, considering the differences in measurement accuracy of sensors, the weighted least-squares (WLS) algorithm can achieve better localization performance than the LS method. Unfortunately, since the coefficient matrix and the noise vector are correlated, the WLS method is biased. The bias-compensation WLS (BCWLS) method is also presented in this paper to reduce the bias by estimating the correlation between the coefficient matrix and the pseudolinear noise vector. To evaluate the performance of the presented algorithms, numerical simulations are conducted, indicating that the superiority of the intersection localization method in computational cost and the superiority of the BCWLS method in localization accuracy.

Three-dimensional spin-wave dynamics, localization and interference in a synthetic antiferromagnet

Spin waves are collective perturbations in the orientation of the magnetic moments in magnetically ordered materials. Their rich phenomenology is intrinsically three-dimensional; however, the three-dimensional imaging of spin waves has so far not been possible. Here, we image the three-dimensional dynamics of spin waves excited in a synthetic antiferromagnet, with nanoscale spatial resolution and sub-ns temporal resolution, using time-resolved magnetic laminography. In this way, we map the distribution of the spin-wave modes throughout the volume of the structure, revealing unexpected depth-dependent profiles originating from the interlayer dipolar interaction. We experimentally demonstrate the existence of complex three-dimensional interference patterns and analyze them via micromagnetic modelling. We find that these patterns are generated by the superposition of spin waves with non-uniform amplitude profiles, and that their features can be controlled by tuning the composition and structure of the magnetic system. Our results open unforeseen possibilities for the study and manipulation of complex spin-wave modes within nanostructures and magnonic devices.

Tensor analysis of tornadoes: a new analytical and numerical model

This research proposes a new mathematical formulation of tornadoes based on the theory of tensor analysis and simulation in a non-inertial dynamics framework, both in two and three dimensions. This model may show the spherical upward movement of air in a tornado without taking into account vertical convection. A tornado requires several elements, including geocentric latitude, the Coriolis effect, increased airspeed in the upper atmosphere, and increased air pressure. Computing the three-dimensional location of the tornado or hurricane, as well as the mathematical models of airflow motion and the Earth's rotation in three-dimensional (3D) space, can determine a tornado's airflow characteristics. To show tornado patterns, we employed computer software that computed motion dynamics and did numerical computations. The results of 2-D modeling and simulation indicated that the greater the initial tornado angular speed, the larger the tornado area. Three-dimensional modeling and simulation also show that tornadoes are more powerful at higher geocentric latitude angles. The novelty of this study is that this model can be used to explain tornado patterns. In our research, we combine tensor analysis, computational modeling, as well as 2D and 3D simulations for simulating tornadoes for the first time. The scientific application of this finding is that researchers at the Meteorology, Climatology, and Geophysics Agency will be able to analyze a tornado and geophysical phenomena more readily with simulations and models.

Navigation system for orchard spraying robot based on 3D LiDAR SLAM with NDT_ICP point cloud registration

Autonomous navigation of orchard spraying robots can effectively improve operational efficiency and reduce workload. The conventional robot navigation solutions based on the Global Navigation Satellite System (GNSS) are susceptible to signal loss in orchards due to interference from the canopy of fruit trees. In this paper, an autonomous navigation scheme for orchard spraying robots based on multi-sensor devices and the three-dimensional (3D) LiDAR Simultaneous Localization and Mapping (SLAM) technology. The initial step of the scheme involved the construction of a 3D point cloud map of the orchard using the 3D LiDAR SLAM algorithm. Subsequently, a designed point cloud map transformation algorithm was used to convert the 3D point cloud map of the orchard into a two-dimensional (2D) grid map containing key feature information of the orchard. To enhance the mapping accuracy of the orchard point cloud, a point cloud registration algorithm combining Iterative Closet Point (ICP) and Normal Distributions Transform (NDT) was proposed. This algorithm initially utilized the NDT algorithm for coarse point cloud registration to obtain transformation parameters. Then, the ICP algorithm was applied in conjunction with the obtained parameters for fine registration. Regarding obstacle avoidance, a cooperative obstacle avoidance algorithm based on the Robot Operating System (ROS) multithreaded communication mechanism was introduced. Experimental trials conducted in a standardized spindle-shaped peach orchard validated the successful completion of the SLAM mapping trajectory, which was achieved through the utilization of the proposed NDT_ICP point cloud registration algorithm. The average absolute pose error between the mapped trajectory and the reference trajectory was 1.173 m, with a standard deviation of 0.498 m. The robot's positioning and navigation errors increased with higher speeds, with the largest positioning deviation observed at 1.2 m/s speed, with a maximum lateral positioning error of 7.04 cm. The robot's average lateral navigation error did not exceed 16 cm, and the average heading deviation was less than 8° at different speeds of 0.4, 0.8 and 1.2 m/s. Both the positioning and navigation accuracies of the robot were sufficient to meet the autonomous operational requirements of orchard spraying robots.

Cone-beam computed tomography of accessory canals of the canalis sinuosus and analysis of the related risk factors.

Cone-beam computed tomography (CBCT) was used in this study for evaluating the diameter, prevalence, spatial location, and risk factors of the accessory canal (AC) of the canalis sinuosus. A comprehensive assessment of the incidence rate, diameter, three-dimensional (3D) spatial location, and direction of travel of AC was performed on 1003 CBCT images. The CBCT data were used to reconstruct a 3D model of the maxilla to determine the alveolar bone volume. The obtained data were further analyzed and processed. AC was present in 50.1% of images. Male patients more frequently had ACs than female patients did (P < 0.01) and was positively correlated with the maxillary alveolar bone volume (P < 0.001, OR 1.532). Age or nasopalatine canal diameter were not significantly associated with the occurrence of AC (P > 0.05). Among the 502 patients with AC, AC was present on the left side, right side, and bilaterally in 189, 98, and 215, respectively. The maximum number of ACs observed per individual was eight. The average AC diameter was 0.89 ± 0.26mm (minimum, 0.5mm; maximum, 2.02mm). As the prevalence of AC and its trajectory display considerable variation among individuals, surgeons must consider the possibility of the presence of AC when devising surgical plans involving the anterior maxillary region.

Large-FOV 3D localization microscopy by spatially variant point spread function generation.

Accurate characterization of the microscopic point spread function (PSF) is crucial for achieving high-performance localization microscopy (LM). Traditionally, LM assumes a spatially invariant PSF to simplify the modeling of the imaging system. However, for large fields of view (FOV) imaging, it becomes important to account for the spatially variant nature of the PSF. Here, we propose an accurate and fast principal components analysis-based field-dependent 3D PSF generator (PPG3D) and localizer for LM. Through simulations and experimental three-dimensional (3D) single-molecule localization microscopy (SMLM), we demonstrate the effectiveness of PPG3D, enabling super-resolution imaging of mitochondria and microtubules with high fidelity over a large FOV. A comparison of PPG3D with a shift-variant PSF generator for 3D LM reveals a threefold improvement in accuracy. Moreover, PPG3D is approximately 100 times faster than existing PSF generators, when used in image plane-based interpolation mode. Given its user-friendliness, we believe that PPG3D holds great potential for widespread application in SMLM and other imaging modalities.

Localising two sub-diffraction emitters in 3D using quantum correlation microscopy

The localisation of fluorophores is an important aspect of determining the biological function of cellular systems. Quantum correlation microscopy (QCM) is a promising technique for providing diffraction unlimited emitter localisation that can be used with either confocal or widefield modalities. However, so far, QCM has not been applied to three dimensional localisation problems. Here we show that QCM provides diffraction-unlimited three-dimensional localisation for two emitters within a single diffraction-limited spot. By introducing a two-stage maximum likelihood estimator, our modelling shows that the localisation precision scales as 1/t where t is the total detection time. Diffraction unlimited localisation is achieved using both intensity and photon correlation from Hanbury Brown and Twiss measurements at as few as four measurement locations. We also compare the results of (MC) simulations with the Cramér–Rao lower bound.

Real-Time Optical Localization and Tracking of UAV Using Ellipse Detection

A real-time three-dimensional (3D) spatial localization system to track a UAV (unmanned aerial vehicle) using a single off-board conventional camera and an onboard circle-shaped colored Light-Emitting Diode (LED) marker is presented. The image from the camera is color-segmented and then morphologically closed before being sent to the ellipse detector. The location of the drone is then estimated with geometric/optical calculations using the pixel coordinates provided by the real-time ellipse detector. The location data generated by this system was validated by a Motion-Capture System (MCS) that was simultaneously tracking the system in real-time. The average position error was of 6cm, while the processing speed achieved 15 locations/second, which are comparable with recent research references. The usage of a low-cost camera makes this method promising for most mobile UAV tracking applications.

Three-dimensional sound source localization system based on fiber optic sensor array with an adaptive algorithm

Sound Source Localization (SSL) based on microphone arrays nowadays is widely used in the fields of machinery rattle localization, weapon navigation, and robot hearing. However, there is also a need for SSL in some special environments, such as long-distance gas pipelines where there is a risk of leakage. In these environments, arrays built with ordinary microphones can be a safety hazard, which can be compensated by the External Fabry-Perot interferometer (EFPI) fiber-optic sensor's advantages of being uncharged, inexpensive, and highly sensitive. To expand the application areas of microphone array-based SSL techniques, this paper using four EFPI fiber-optic sensors to constructs a 1 m × 1 m × 1 m sensor array, which is used for real-time localization of sound sources based on three-wavelength adaptive intensity demodulation methods and Time Difference Of Arrival (TDOA) localization techniques. An improved method is proposed for the three-wavelength adaptive intensity demodulation method to avoid the occurrence of signal flips. Finally, formulas are provided for this sensor array to quickly calculate the sound source position based on the arrival delay. Several experiments show that the system can achieve sound source localization over a wide range with an average error of less than 3 cm.

Chromatin structure from high resolution microscopy: Scaling laws and microphase separation.

Recent advances in experimental fluorescence microscopy allow high accuracy determination (resolution of 50nm) of the three-dimensional physical location of multiple (up to ∼10^{2}) tagged regions of the chromosome. We investigate publicly available microscopy data for two loci of the human Chr21 obtained from multiplexed fluorescence in situ hybridization (FISH) methods for different cell lines and treatments. Inspired by polymer physics models, our analysis centers around distance distributions between different tags with the aim being to unravel the chromatin conformational arrangements. We show that for any specific genomic site, there are (at least) two different conformational arrangements of chromatin, implying coexisting distinct topologies which we refer to as phase α and phase β. These two phases show different scaling behaviors: the former is consistent with a crumpled globule, while the latter indicates a confined, but more extended conformation, such as a looped domain. The identification of these distinct phases sheds light on the coexistence of multiple chromatin topologies and provides insights into the effects of cellular context and/or treatments on chromatin structure.

Quantifying nanoscopic alterations associated with mitochondrial dysfunction using three-dimensional single-molecule localization microscopy.

Mitochondrial morphology provides unique insights into their integrity and function. Among fluorescence microscopy techniques, 3D super-resolution microscopy uniquely enables the analysis of mitochondrial morphological features individually. However, there is a lack of tools to extract morphological parameters from super-resolution images of mitochondria. We report a quantitative method to extract mitochondrial morphological metrics, including volume, aspect ratio, and local protein density, from 3D single-molecule localization microscopy images, with single-mitochondrion sensitivity. We validated our approach using simulated ground-truth SMLM images of mitochondria. We further tested our morphological analysis on mitochondria that have been altered functionally and morphologically in controlled manners. This work sets the stage to quantitatively analyze mitochondrial morphological alterations associated with disease progression on an individual basis.

Multi-Dimensional Wi-Fi Received Signal Strength Indicator Data Augmentation Based on Multi-Output Gaussian Process for Large-Scale Indoor Localization

Location fingerprinting using Received Signal Strength Indicators (RSSIs) has become a popular technique for indoor localization due to its use of existing Wi-Fi infrastructure and Wi-Fi-enabled devices. Artificial intelligence/machine learning techniques such as Deep Neural Networks (DNNs) have been adopted to make location fingerprinting more accurate and reliable for large-scale indoor localization applications. However, the success of DNNs for indoor localization depends on the availability of a large amount of pre-processed and labeled data for training, the collection of which could be time-consuming in large-scale indoor environments and even challenging during a pandemic situation like COVID-19. To address these issues in data collection, we investigate multi-dimensional RSSI data augmentation based on the Multi-Output Gaussian Process (MOGP), which, unlike the Single-Output Gaussian Process (SOGP), can exploit the correlation among the RSSIs from multiple access points in a single floor, neighboring floors, or a single building by collectively processing them. The feasibility of MOGP-based multi-dimensional RSSI data augmentation is demonstrated through experiments using the hierarchical indoor localization model based on a Recurrent Neural Network (RNN)—i.e., one of the state-of-the-art multi-building and multi-floor localization models—and the publicly available UJIIndoorLoc multi-building and multi-floor indoor localization database. The RNN model trained with the UJIIndoorLoc database augmented with the augmentation mode of “by a single building”, where an MOGP model is fitted based on the entire RSSI data of a building, outperforms the other two augmentation modes and results in the three-dimensional localization error of 8.42 m.

Enhanced Dynamic Surface EMG Decomposition Using the Non-Negative Matrix Factorization and Three-Dimensional Motor Unit Localization.

Surface electromyography (sEMG) signal decomposition is of great importance in examining neuromuscular diseases and neuromuscular research, especially dynamic sEMG decomposition is even more technically challenging. A novel two-step sEMG decomposition approach was developed. The linear minimum mean square error estimation was first employed to extract estimated firing trains (EFTs) from the eigenvector matrices constructed using the non-negative matrix factorization (NMF). The firing instants of each EFT were then classified into motor units (MUs) according to their specific three-dimensional (3D) space position. The performance of the proposed approach was evaluated using simulated and experimentally recorded sEMG. The simulation results demonstrated that the proposed approach can reconstruct MUAPTs with true positive rates of 89.12 ± 2.71%, 94.34 ± 1.85% and 95.45 ± 2.11% at signal-to-noise ratios of 10, 20, and 30 dB, respectively. The experimental results also demonstrated a high decomposition accuracy of 90.13 ± 1.31% in the two-source evaluation, and a high accuracy of 91.86 ± 1.14% in decompose-synthesize-decompose- compare evaluation. The adoption of NMF reduces the dimension of random pattern under the restriction of non-negativity, as well as keeps the information unchanged as much as possible. The 3D space information of MUs enhances the classification accuracy by tackling the issue of relative movements between MUs and electrodes during dynamic contractions. The accuracy achieved in this study demonstrates the good performance and reliability of the proposed decomposition algorithm in dynamic surface EMG decomposition. The spatiotemporal information is applied to the dynamic surface EMG decomposition.

Completion Time Optimization in UAV-Relaying-Assisted MEC Networks With Moving Users

As one of the most popular consumer electronics, Unmanned Aerial Vehicle (UAV) has the potential to assist User Equipment (UE) in the Internet of Everything. Mobile edge computing (MEC) is also an emerging technique that can provide sufficient computing resources to IoE users. In this paper, we focused on the UAV-assisted MEC problem with mobile UEs, where the UAV serves as an MEC server to assist UEs in computing and acts as a relay to deliver tasks to a ground access point (AP). The objective is to minimize the average time for completing all tasks in the network while jointly optimizing resource allocation such as communication bandwidth, CPU frequency, task division ratio, and UAV’s three-dimensional location deployment. First, we proposed an online MEC network adjustment scheme. Then, we decomposed the formulated non-convex problem into three low-complexity subproblems. Last, we proposed a successive convex approximation-based joint optimization algorithm to solve them. In addition, we presented heuristic conclusions in task allocation rules, UAV flight trajectory prediction, and UAV hovering altitude selection, which can further reduce task completion time and deepen the understanding of the working mode of mobile edge servers. Simulation results show that the algorithm can significantly reduce the completion time.

Muography as a support technique for non-invasive research and three-dimensional localization of tombs in archaeological sites: a case study from Palazzone Necropolis (Perugia – Italy)

Transmission muography is a non-invasive imaging technique that exploits the penetrating power of atmospheric muons into matter to obtain two-dimensional and three-dimensional density images of the monitored structure. The detectors used are particle trackers. Muography enables the monitoring of large structures and it is also particularly useful in the archaeological field for a mapping of low-density underground anomalies potentially related to unknown or inaccessible tombs or tunnels. The Palazzone necropolis, located south of Perugia (Italy), dating back to Etruscan period, contains about 200 known tombs, some of which, such as the Volumni Hypogeum, can be visited thanks to a touristic route. The eastern area of the necropolis, on the other hand, does not have a touristic path and is partially unknown. The objective of the muographic measurement campaign is to support the re-evaluation of this archaeological area by searching for new anthropic cavities and identifying them three-dimensionally. One of the goals of this study is to obtain a three-dimensional localization of cavities starting from a single muographic measurement by exploiting an image focusing algorithm. For this purpose, an area that contains a known cavity was used as the reference cavity for the test of the three-dimensional reconstruction algorithm.

Evaluation of tumor microvasculature with 3D ultrasound localization microscopy based on 2D matrix array.

Evaluation of tumor microvascular morphology is of great significance in tumor diagnosis, therapeutic effect prediction, and surgical planning. Recently, two-dimensional ultrasound localization microscopy (2DULM) has demonstrated its superiority in the field of microvascular imaging. However, it suffers from planar dependence and is unintuitive. We propose a novel three-dimensional ultrasound localization microscopy (3DULM) to avoid these limitations. We investigated 3DULM based on a 2D array for tumor microvascular imaging. After intravenous injection of contrast agents, all elements of the 2D array transmit and receive signals to ensure a high and stable frame rate. Microbubble signal extraction, filtering, positioning, tracking, and other processing were used to obtain a 3D vascular map, flow velocity, and flow direction. To verify the effectiveness of 3DULM, it was validated on double helix tubes and rabbit VX2 tumors. Cisplatin was used to verify the ability of 3DULM to detect microvascular changes during tumor treatment. In vitro, the sizes measured by 3DULM at 3mm and 13mm were 178 [Formula: see text] and 182 [Formula: see text], respectively. In the rabbit tumors, we acquired 9000 volumes to reveal vessels about 30 [Formula: see text] in diameter, which surpasses the diffraction limit of ultrasound in traditional ultrasound imaging, and the results matched with micro-angiography. In addition, there were significant changes in vascular density and curvature between the treatment and control groups. The effectiveness of 3DULM was verified in vitro and in vivo. Hence, 3DULM may have potential applications in tumor diagnosis, tumor treatment evaluation, surgical protocol guidance, and cardiovascular disease. 3D ultrasound localization microscopy is highly sensitive to microvascular changes; thus, it has clinical potential for tumor diagnosis and treatment evaluation. • 3D ultrasound localization microscopy is demonstrated on double helix tubes and rabbit VX2 tumors. • 3D ultrasound localization microscopy can reveal vessels about 30 [Formula: see text] in diameter-far smaller than traditional ultrasound. • This form of imaging has potential applications in tumor diagnosis, tumor treatment evaluation, surgical protocol guidance, and cardiovascular disease.

A superficial dissection approach to the sphenopalatine (pterygopalatine) ganglion to emphasize osteopathic clinical relevance.

The sphenopalatine (pterygopalatine) ganglion (SPG) is the most superficial ganglia to manipulate from the oral cavity. It has parasympathetic and sensory fibers directly affecting the paranasal sinuses as well as the palatine, nasal, pharyngeal, and lacrimal glands. The SPG can be manipulated intraorally by students and physicians utilizing osteopathic manipulative treatment (OMT) to relieve congestion associated with sinusitis, allergies, headaches, and upper respiratory infections. Within osteopathic medical education programs, students have anecdotally had difficulty identifying this ganglion due to its deep anatomic location and lack of direct visualization. In thisarticle, we discuss that cadaveric dissection with a superficial to deep approach to the SPG has the ability to allow medical students and physicians to better understand the three-dimensional location and osteopathic clinical relevance of this ganglion.