Navigation Applications Research Articles

An Algorithm for Affordable Vision-Based GNSS-Denied Strapdown Celestial Navigation

Celestial navigation is rarely seen in modern Uncrewed Aerial Vehicles (UAVs). The size and weight of a stabilized imaging system, and the lack of precision, tend to be at odds with the operational requirements of the aircraft. Nonetheless, celestial navigation is one of the few non-emissive modalities that enables global navigation over the ocean at night in Global Navigation Satellite System (GNSS) denied environments. This study demonstrates a modular, low cost, lightweight strapdown celestial navigation solution that is utilized in conjunction with Ardupilot running on a Cube Orange to produce position estimates to within 4 km. By performing an orbit through a full rotation of compass heading and averaging the position output, we demonstrate that the biases present in a strapdown imaging system can be nullified to drastically improve the position estimate. Furthermore, an iterative method is presented which enables the geometric alignment of the camera with the Attitude and Heading Reference System (AHRS) in-flight without an external position input. The algorithm is tested using real flight data captured from a fixed wing aircraft. The results from this study offer promise for the application of low cost celestial navigation as a redundant navigation modality in affordable, lightweight drones.

Design and Performance Analysis of Dielectric Resonator Antenna Array for 5G mm-Wave Ground-Based Navigation and Wireless Applications

Design and Performance Analysis of Dielectric Resonator Antenna Array for 5G mm-Wave Ground-Based Navigation and Wireless Applications

The Evolving Role Of Artificial Intelligence In Neurosurgical Planning And Outcome Prediction: A MetaAnalysis

Artificial Intelligence (AI) is transforming various medical fields, including neurosurgery. This review explores the evolving role of AI in neurosurgical planning and outcome prediction, with a focus on its applications in preoperative imaging, intraoperative navigation, and postoperative outcome forecasting. A meta-analysis of recent studies shows that AI enhances precision, reduces errors, and offers personalized patient care. However, significant challenges such as interpretability and integration into clinical practice remain. This article discussescurrent developments, limitations, and future innovations in the use of AI in neurosurgery.

Concurrent Access Performance Comparison Between Relational Databases and Graph NoSQL Databases for Complex Algorithms

Databases are a fundamental element of contemporary software applications. The most widely used and recognized type in practice is the relational database, valued for its ability to store and organize data in tabular structures, its emphasis on data consistency and integrity, and its use of a standardized query language, SQL. However, with the rapid increase in both the volume and complexity of data, relational databases have recently encountered challenges in effectively modeling this expanding information. To address performance challenges, new database systems have emerged, offering alternative approaches to data modeling—these are known as NoSQL databases. In this paper, we present an indoor navigation application designed to operate on both a relational database, Microsoft SQL Server, and a graph-based NoSQL database, Neo4j. We describe the algorithms implemented for testing and the performance metrics analyzed to draw our conclusions. The results revealed Neo4j’s strength in managing data with complex relationships but also exposed its limitations in handling concurrent access, where SQL Server demonstrated significantly greater stability.

Multi-Buoy Deployment Method Based on an Improved Tuna Swarm Optimizer Enhanced with Fractional-Order Calculus Method for Marine Observation

Ocean buoys play a critical role in marine hydrological, water quality, and meteorological monitoring, with applications in navigation, environmental observation, and communication. However, accurately modeling and deploying a multi-buoy system in the complex marine environment presents significant challenges. To address these challenges, this study proposes an enhanced deployment strategy using the tuna swarm optimizer enhanced with the fractional-order calculus method for marine observation. The proposed method first introduces a detailed observation model that precisely captures the performance of buoys in terms of coverage and communication efficiency. By integrating the observation coverage ratio and communication energy consumption, we establish an optimal multi-buoy deployment model. The proposed method leverages tent chaotic mapping to improve the diversity of initial solution generation and incorporates fractional-order calculus to strengthen its search capabilities. Simulation experiments and statistical analysis verify the effectiveness of the proposed deployment model, with the proposed method achieving the best performance in deploying the multi-buoy system, reaching a final fitness value of 0.190052 at iteration 449, outperforming TSA, PSO, GWO, and WOA. These results highlight the potential of the proposed method in optimizing multi-buoy system deployment in marine observation.

Design and Analysis of Sierpinski Fractal Antennas for Millimeter‐Wave 5G and Ground‐Based Radio Navigation Applications

ABSTRACTThe paper describes compact fractal antennae combined with ground defected structures (DGS) and substrate integrated waveguide (SIW) techniques for enhancing resonate and multiband behavior concerning bandwidth, gain, and radiation in the desired mm‐wave region. Based on the proposed antennae, multiple good notches over wide bands depict a good radiation pattern. The antennae's ultra wide bandwidths (UWB) are 16, 16, and 11.4 GHz concerning resonant frequencies 26.34, 30.35, 34.5, 36.65 GHz; 25.8, 32.2, 35.3 GHz; 30.22, 37.68 GHz, of concerning antennae ant 1 (FA1), 4 (FA2), and 6 (FA3), respectively. The proposed antenna (FA3) with the SIW technique has a peak gain of 5.9 dBi and a peak front‐to‐back ratio of 20 dB, respectively. The proposed antennas are targeted to cover the practical contribution aspect, including advanced 5G bands support (24–40 GHz), broadband spectrum, frequency agility, low 3 dB beamwidth, interference reduction, and medical application suitability, respectively. The proposed antennae also cover the desired mm wave 5G region with different resonating notches over ultra‐wide bandwidth, such as n257, n258, n259, n260, and n261, and ground‐based radio navigation applications. Results are validated with vector network analyzer, spectrum analyzer, and power sensor in the presence of absorber, respectively.

Cross-Spectral Navigation with Sensor Handover for Enhanced Proximity Operations with Uncooperative Space Objects

Close-proximity operations play a crucial role in emerging mission concepts, such as Active Debris Removal or small celestial bodies exploration. When approaching a non-cooperative target, the increased risk of collisions and reduced reliance on ground intervention necessitate autonomous on-board relative pose (position and attitude) estimation. Although navigation strategies relying on monocular cameras which operate in the visible (VIS) spectrum have been extensively studied and tested in flight for navigation applications, their accuracy is heavily related to the target’s illumination conditions, thus limiting their applicability range. The novelty of the paper is the introduction of a thermal-infrared (TIR) camera to complement the VIS one to mitigate the aforementioned issues. The primary goal of this work is to evaluate the enhancement in navigation accuracy and robustness by performing VIS-TIR data fusion within an Extended Kalman Filter (EKF) and to assess the performance of such navigation strategy in challenging illumination scenarios. The proposed navigation architecture is tightly coupled, leveraging correspondences between a known uncooperative target and feature points extracted from multispectral images. Furthermore, handover from one camera to the other is introduced to enable seamlessly operations across both spectra while prioritizing the most significant measurement sources. The pipeline is tested on Tango spacecraft synthetically generated VIS and TIR images. A performance assessment is carried out through numerical simulations considering different illumination conditions. Our results demonstrate that a combined VIS-TIR navigation strategy effectively enhances operational robustness and flexibility compared to traditional VIS-only navigation chains.

Intraoperative navigation in craniofacial surgery.

Craniofacial surgery requires comprehensive anatomical knowledge of the head and neck to ensure patient safety and surgical precision. Over recent decades, there have been significant advancements in imaging techniques and the development of real-time surgical navigation systems. Intraoperative navigation technology aligns surgical instruments with imaging-derived information on patient anatomy, enabling surgeons to closely follow preoperative plans. This system functions as a radiologic map, improving the accuracy of instrument placement and minimizing surgical complications. The introduction of first-generation navigation systems in the early 1990s revolutionized surgical procedures by enabling real-time tracking of instruments using preoperative imaging. Initially utilized in neurosurgery, intraoperative navigation has since become standard practice in otolaryngology, cranio-maxillofacial surgery, and orthopedics. Since the 2000s, second-generation navigation systems have been developed to meet the growing demand for precision across various surgical specialties. The adoption of these systems in craniofacial surgery has been slower, but their use is increasing, particularly in procedures such as foreign body removal, facial bone fracture reconstruction, tumor resection, and craniofacial reconstruction and implantation. In Korea, insurance coverage for navigation in craniofacial surgery began in 2021, and new medical technologies for orbital wall fracture treatment were approved in August 2022. These technologies have only recently become clinically available, but are expected to play an increasingly important role in craniofacial surgery. Intraoperative navigation enhances operative insight, improves target localization, and increases surgical safety. Although these systems have a steep learning curve and initially prolong surgery, efficiency improves with experience. Calibration issues, registration errors, and soft tissue deformation can introduce inaccuracies. Nonetheless, navigation technology is evolving, and the integration of intraoperative computed tomography data holds promise for further enhancements of surgical accuracy. This paper discusses the various types and applications of navigation employed in craniofacial surgery, highlighting their benefits and limitations.

The ambivalent relationship of e-scooters and public transport: Evidence from France

This paper aims at assessing competitiveness of shared e-scooters relative to public transport proposing a methodology that uses empirical data at the individual trip level and comparing e-scooter trips with the alternative public transit route available to the traveler at the time of the trip, as estimated by a navigation and public transit application. This allows us to obtain information at the individual transit trip level, such as in-vehicle time, walking, waiting, and other. We then explore the competitiveness between the two alternatives using two performance measures – travel time (TT) and an estimation of the generalized cost (GC) of a trip – for different levels of aggregation. Results show that in general, e-scooters are more competitive in terms of travel time. However, due to the higher pricing, generalized cost of transit is generally lower than that of e-scooter. In 60% of the cases users would lower their generalized cost by using public transport instead of e-scooter. On average, e-scooter is a better option for trips up to 15min, while public transit is better for longer trips. They are also more competitive during hours when transit frequency is reduced, as well as in areas with reduced service. Finally, we also find that one in five trips complement public transport service offering transportation outside of transit service hours or between areas with no connectivity. Further research should include surveys in order to obtain more details on the psychological constructs of the users.

Blind indoor navigation app for enhancing accessible tourism in smart cities

Purpose People with visual impairments or blindness (PwVIB) are mostly excluded from tourism activities. Despite the rise of assistive technology (AT) solutions in Tourism, acceptance remains low because of the difficulty of providing the right functionality, effectiveness and usability. Arguably, it can be said that disability-oriented training can affect the latter two and, therefore, an AT solution’s acceptance. This paper aims to contribute to the theory development and conceptualization of technology acceptance of AT solutions in Tourism by studying, in the context of the Unified Theory of Acceptance and Use of Technology (UTAUT), the effects of training PwVIB on using AT solutions. This study presents the effects of training on the tourism behavior of PwVIB and provides valuable information to the stakeholders. Design/methodology/approach Questionnaire data collected from 128 PwVIB after evaluating an AT were subjected to exploratory and confirmatory factor analysis and structural equation modeling followed by post-evaluation interviews. The used application, called BlindMuseumTourer, enables high-precision autonomous indoor navigation for PwVIB in tourist places like museums and places of health care. Findings The results of this study indicate the partial satisfaction of the extended model validating the importance of performance expectancy and training (the new factor) in predicting the behavioral intention of PwVIB tourists toward using ATs during their tourist activities. This suggests that practitioners have to provide performant technological solutions accompanied by special training sessions for improved engagement and satisfaction. Originality/value This study contributes to the UTAUT theory in the context of Tourism for PwVIB by adding a new factor and replacing two moderator variables. To the best of the authors’ knowledge, no similar work is studying AT acceptance by PwVIB in the tourism literature. Furthermore, the validation process used a novel indoor navigation application, demonstrating its effectiveness in the Tactual Museum of Greece.

Design and analysis of graphene-based PBG and EBG array antennas for wideband and multiband mm-wave applications

This paper presents a graphene-based PBG, EBG array antenna design with 40 × 40 mm2 dimensions for wide and multiband applications. The corporate CPW (Coplanar Waveguide) feeding technique is integrated with the ring, meander line, and periodic staircase with a slot pattern and augmented by conductive graphene for Electromagnetic Band Gap and Photonic Band Gap structures on the opposite side. This integration significantly enhances antenna performance, manifesting in superior radiation properties, increased gain, enhanced directivity, and resonating behavior with return loss of 16.4, 21.7, and 22.45 27.0, 25.3 dB in range of 24–25.25 GHz, 26.29–28.1 GHz, and 28.8–35.95 GHz and five bands with return loss of 26.1 , 21.1 , 22.2 , 31 , and 15.5 dB in range of 25.28–26.25, 28.1–29.4, 30.7–33.5, 34–35.5, 36.2–40.0 GHz that covers wideband and Multiband applications concerning PBG and EBG structures, respectively. Furthermore, the proposed antennae exhibit peak gains of 8 dBi at 26.53 GHz and 9 dBi at 32 GHz, corresponding 86.1% and 79.4% peak efficiencies and ensure robust circular polarization at resonating notches cover the mm-Wave 5G frequency bands n257, n258, n259, n260, and n261 for 5G applications, supporting ultra-fast data rates and low-latency communication with ground-based radio navigation applications.

Sentiment Analysis of Google Maps User Reviews on the Play Store Using Support Vector Machine and Latent Dirichlet Allocation Topic Modeling

These days, traveling is made easier by utilizing easily accessible online directions such as Google Maps. Google Maps provides real-time routes by displaying and presenting the closest routes that users can take. However, lately, the routes provided by Google Maps services often get users lost by presenting routes such as forests, narrow roads, and even dead ends. Therefore, this study aims to determine the level of user satisfaction and sentiment into two categories, namely positive and negative, based on reviews on the Google Play Store platform using the Support Vector Machine (SVM) algorithm and topic modeling using Latent Dirichlet Allocation (LDA) to find out the collection of topics that are the main topics of conversation by users regarding Google Maps services. The results of this study show that the SVM algorithm is feasible to use in sentiment analysis classification with an accuracy value of 86%, precision of 93%, recall of 53%, and f1-score of 52%. In addition, topic modeling is applied to generate coherence values for each topic, which shows that the higher the coherence value, the more specific the topic is. The highest coherence value generated in this study was two topic models with a coherence value of 35.15%, but this study took five with a coherence value of 33.39%. The five topic models to be applied in this study are selected because they have a good enough coherence value to identify the main topics and hidden topics in Google Maps user reviews with the Latent Dirichlet Allocation model. The topic model shows five aspects users often discuss: Google Maps route accuracy, system and service errors, navigation application directions, lost time history, and convoluted route provision.

Design and Performance Analysis of Graphene Integrated CPW Fed Fractal Antennae for 5G mm-Wave and Ground Based Navigation Applications

Design and Performance Analysis of Graphene Integrated CPW Fed Fractal Antennae for 5G mm-Wave and Ground Based Navigation Applications

Path Tracing-Inspired Modeling of Non-Line-of-Sight SPAD Data.

Non-Line of Sight (NLOS) imaging has gained attention for its ability to detect and reconstruct objects beyond the direct line of sight, using scattered light, with applications in surveillance and autonomous navigation. This paper presents a versatile framework for modeling the temporal distribution of photon detections in direct Time of Flight (dToF) Lidar NLOS systems. Our approach accurately accounts for key factors such as material reflectivity, object distance, and occlusion by utilizing a proof-of-principle simulation realized with the Unreal Engine. By generating likelihood distributions for photon detections over time, we propose a mechanism for the simulation of NLOS imaging data, facilitating the optimization of NLOS systems and the development of novel reconstruction algorithms. The framework allows for the analysis of individual components of photon return distributions, yielding results consistent with prior experimental data and providing insights into the effects of extended surfaces and multi-path scattering. We introduce an optimized secondary scattering approach that captures critical multi-path information with reduced computational cost. This work provides a robust tool for the design and improvement of dToF SPAD Lidar-based NLOS imaging systems.

Application of augmented reality navigation in oral surgery. A clinical trial.

Background. Augmented reality (AR) is a potential alternative for surgical navigation, as it can provide visualisation of various anatomical structures of maxilla-facial region.We have developed a specific platform for 3D model management and intraoperative AR-navigation during surgical procedures. Objective. The aim of this study was to evaluate the surgeons’ perceptions and usability of AR- navigation for most common surgical procedures in oral surgery. Materials and Methods. We performed a phantom study to determine the accuracy of the AR system in the maxillofacial region. Registration errors are typical in image-guided surgery were measured: Fiducial Registration Error (FRE), Target Registration Error (TRE), and Fiducial Localization Error (FLE). Thereafter we conducted a clinical trial with several surgeons performing surgical procedures on jaws using AR-technology. AR- navigation usability was evaluated with the User Experience Questionnaire (UEQ) (scores range from -3 to +3 for each scale). Results. Mean value of the Fiducial Registration Error was 0.9 mm with SD = 0.7 mm (95% CI 0.4–1.3 mm). Target Registration Error was 1.3 mm (SD= 0.5 mm, 95% CI 1.1–1.5 mm). Fiducial Localization Error was the most significant – 2.2mm (SD= 0.9, 95% CI 1.9–2.5 mm). The higher rankings in the UEQ were related to the novelty and excitement of using an AR-navigation in maxillofacial surgery. The pragmatic quality aspect explains the technical focus of perception to achieve goals in a product, system, or service design. Efficiency was expected to be slightly higher, but in our opinion this is due to the technical difficulties of the system for novel AR technology. Conclusion. Based on our results, accuracy of the AR system in the maxillofacial region and the user experience of the AR-navigation system for oral surgery is good enough.

Performance Evaluation of a Bioinspired Geomagnetic Sensor and Its Application for Geomagnetic Navigation in Simulated Environment.

For geomagnetic navigation technology, taking inspiration from nature and leveraging the principle of animals' utilization of the geomagnetic field for long-distance navigation, and employing biomimetic technology to develop higher-precision geomagnetic sensors and more advanced navigation strategies, has emerged as a new trend. Based on the two widely acknowledged biological magnetic induction mechanisms, we have designed a bioinspired weak magnetic vector (BWMV) sensor and integrated it with neural networks to achieve geomagnetic matching navigation. In this paper, we assess the performance of the BWMV sensor through finite element model simulation. The result validates its high measurement accuracy and outstanding adaptability to installation errors with the assistance of specially trained neural networks. Furthermore, we have enhanced the bioinspired geomagnetic navigation algorithm and proposed a more advanced search strategy to adapt to navigation under the condition of no prior geomagnetic map. A simulated geomagnetic navigation platform was constructed based on the finite element model to simulate the navigation of the BWMV sensor in geomagnetic environments. The simulated navigation experiment verified that the proposed search strategy applied to the BWMV sensor can achieve high-precision navigation. This study proposes a novel approach for the research of bioinspired geomagnetic navigation technology, which holds great development prospects.

CMOS-compatible plasmonic magnetic field sensor: An alternative approach using ultra-compact MIM configuration

This paper introduces a novel magnetic field sensor (MFS) that utilizes a metal-insulator-metal (MIM) waveguide integrated with a resonator structure and incorporates water-based Fe3O4 magnetic fluid. The sensor uses titanium nitride (TiN) as the plasmonic material which offers numerous advantages over conventional noble plasmonic materials. The sensor takes advantage of the tunable optical properties of the magnetic fluid and TiN to detect changes in the external magnetic field and quantify the magnetic field strength which has been demonstrated using the Finite Element Method (FEM). Our proposed MFS exhibits a high sensitivity of 11.97 pm/Oe, a narrow-band full-width half maximum of 93.66 nm, and a resolution of 8.36 × 10−4 Oe. The sensor is also compatible with complementary metal oxide semiconductor (CMOS) fabrication techniques, which enables chip-scale integration and low-cost production. The sensor can be used for various applications in navigation, military, space, healthcare, and beyond.

High-resolution regional sea-ice model based on the discrete element method with boundary conditions from a large-scale model for ice drift

Abstract Understanding sea-ice dynamics at the floe scale is crucial to comprehend polar climate systems. While continuum models are commonly used to simulate large-scale sea-ice dynamics, they have limitations in accurately representing sea-ice behaviour at small scales. DEMs, on the other hand, are well-suited for modelling the behaviour of individual ice floes but face limitations due to computational constraints. To address the limitations of both approaches while combining their strengths, we explored the feasibility of using a DEM within a continuum model, where the latter provides boundary conditions for a rectangular high-resolution DEM domain. This paper presents a feasibility study where a discrete model of a 100 × 100 km2 icefield was created using high-resolution optical satellite imagery. Sea-ice dynamics were simulated in the DEM considering environmental forces and integrating large-scale ice-drift velocities as boundary conditions. Model predictions were compared with satellite observations for ice drift and deformation parameters. This numerical approach showed potential for offering accurate, high-resolution predictions of sea ice, particularly in coastal areas and near islands, and may find applications in ice navigation and climate studies. However, further development of the DEM, along with upgrades to the coupled ocean models providing data for the ice component, may be necessary. Additionally, challenges remain to develop a two-way coupling between the DEM and a continuum model, which may be needed to improve the accuracy of large-scale simulations.

Accuracy assessment of recent global ocean tide models in coastal waters of the European North West Shelf

The accuracy of global ocean tide models is assessed in coastal waters of the European North West Shelf to ascertain where higher resolution local (forecast) models are most needed for geophysical and navigational applications, and which global models are most suitable for providing boundary conditions for regional and local tide models. Five recent global ocean tide models (FES2014b, EOT20, TPXO9-atlas-v5, GOT4.10c, and DTU16) are considered, with the models first compared by interpolating them onto common grids and computing the mean absolute deviation at each grid point. Coastline tide gauge and offshore bottom pressure sensor data were collated from several sources to give a total of 279 observation sites for evaluating model accuracy, including observational values from 137 locations that have not previously been released and have therefore not been assimilated into any of the global models tested. The residual errors between each model’s predicted phasor and the corresponding observed phasor were calculated at each observation location, and quantified using the root mean square (RMS) and median absolute residual (MAR) for the eight tidal constituents M2, S2, N2, O1, K1, K2, P1, and Q1. To avoid RMS values being biased by observation point density, a Voronoi-weighted RMS based on the water area of the Voronoi polygon about each observation location was also developed and used. Four zones were defined based on ocean depth to gauge model performance, and model inaccuracy is again demonstrated in near-shore regions. Seven further zones were defined based on geographical areas, which reveals inhomogeneity among the global models. The smallest overall root sum square (RSS) RMS error across all eight constituents arises with FES2014b, although TPXO9-atlas-v5 has the best performance when using the MAR and Voronoi-weighted RMS metrics. Using only the 137 observation sites that have not been assimilated by any model and therefore provide an independent accuracy assessment, FES2014b exhibits the smallest errors at the coastline, with an RSS RMS of 24.46 cm. All models exhibit larger errors with the 137 independent observation sites than with all 279 observation sites, with an average overall increase in RSS RMS error of 12%, and an increase of 30% for coastline tide gauges, highlighting the need for local model development in these areas.

Design and experiment of Beidou satellite navigation railway tunnel coverage enhancement system

Abstract In areas of satellite navigation signals being obstructed, coveraging the interior of the tunnel with Satellite navigation signals based on navigation signals real-time regeneration technology is an important way to achieve the applications of satellite navigation in railway mobile equipment positioning and auxiliary protection for operators. We analyzed the application requirements on navigation positioning and time synchronization, and technical requirements on universality and electromagnetic compatibility, etc. The article designed the composition and logical architecture of the Beidou satellite navigation railway tunnel coverage enhancement system, proposed the design of system functions and performance parameters, and verified the system’s functionality and performance through static mode testing and dynamic mode testing. The design and implementation of the Beidou satellite navigation railway tunnel coverage enhancement system have important practical value for the application in mobile equipment positioning and auxiliary protection for operators in railway tunnel.