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• Driver unfamiliarity with paper maps and north-up orientation. • Greater route learning with paper map than electronic map or augmented reality. • Driver behavior suggests less uncertainty when using augmented reality. • Greatest benefit from augmented reality when route learning is not a priority. Current trends point towards the development and implementation of augmented reality (AR) navigation assistance systems for drivers. Previous research has found augmented reality can benefit driving performance, but the impact of AR on route learning (spatial knowledge acquisition) has received less attention. The current study used simulated driving scenarios to determine how the type of navigation aid device used (i.e., paper map, electronic map, and AR system) affected driving performance and route learning of 62 driving adults. Route learning was examined at landmark, route, and survey levels. The hypotheses tested were that AR would improve driving performance but diminish route learning compared to paper map use; and that AR would outperform electronic map use in both driving performance and route learning. Results indicated that paper map use led to poorer driving performance and greater route learning. However, map recognition may have been a confounding factor in higher level spatial knowledge acquisition with paper map use. Driving performance and route learning were similar for drivers using the electronic map and AR, but some differences suggested that drivers have reduced uncertainty and hesitation while using AR to navigate in unfamiliar areas. [ABSTRACT FROM AUTHOR]

Dimethylsulfoniopropionate (DMSP) is a ubiquitous organosulfur compound with key ecological roles in marine environments. This paper offers a brief insight into the mechanisms, environmental diversity, and importance of DMSP-mediated marine microbial interactions, including algae–microzooplankton interactions, bacteria–microzooplankton interactions, and algae–bacteria interactions. We also highlight current challenges that warrant further investigation. [ABSTRACT FROM AUTHOR]

In this paper, we address modelling and simulation of dynamics involved in docking of large marine vessels with aid of tugboats, with the aim of providing a tool for improved design of control algorithms for autonomous docking operations. Mathematical models of the docking vessel and tugboats in 3DOF are derived, with a special focus on realistic interactions through towline, contact and friction forces with stick–slip dynamics and time delays, which are typically not considered in previous publications on the topic. We also present the implementation of the developed models in the first step towards a Simulink simulator in which considers the special case of tugboat-assisted docking operations in the Narvik harbour. The developed simulator is available on GitHub (see Ørke et al. (2023)) and encompasses model dynamics, tugboat control and vessel control and guidance, although the scope of this paper is model dynamics. We present simulation results that show that we are indeed able to capture interaction dynamics in a realistic way. Finally, we include a discussion of our results and some ideas for further development, as well as some concluding remarks. [Display omitted] • Mathematical modelling of docking vessel and tugboats in 3DOF. • Modelling of interaction forces in pushing/pulling operations. • Model implementation in Simulink-developed simulator. • Simulation and discussion of interaction forces, and ideas for future work. [ABSTRACT FROM AUTHOR]

Fiber-optic hydrophones based on optical fiber sensing and communication technology have developed rapidly in recent years. With the advantages of high sensitivity, small size, and large dynamic range, they are easy to detect underwater acoustic signals, showing great potential in the field of marine ecological protection. Researchers can monitor the marine ecological environment by recognizing underwater optical fiber sensing signals collected by fiber-optic hydrophones in real-time. Deep learning models can achieve high recognition accuracy, but they usually have large amounts of parameters that makes them difficult to be deployed in mobile terminals of marine survey ships. To solve the key problem, this paper discussed the design of the Deep Light-Weight Attention Residual Network (DLA-ResNet). It introduces the depth-wise separable convolution (DSC) and the convolutional block attention module (CBAM) into ResNet18 to make its performance better. ResNet18 is a two-dimensional convolutional network (CNN) model applying residual blocks. Experiments verify that the accuracy of DLA-ResNet improved from ResNet18 is increased by about 2.04% and its size is reduced by 85.67%. The proposed scheme in this paper realizes an average recognition rate of 96.50% for eight types of underwater optical fiber sensing signals in the application of marine ecological environment monitoring. Moreover, its model size is only 6.12 MB and it only takes 27.90 ms, which is available to meet the needs of reliability and effectiveness. [ABSTRACT FROM AUTHOR]

• Availability area analysis of distance measuring equipment global network. • Service volume is estimated based on path loss model. • Distance measuring equipment. • DME service can be provided only in 27.76% of global airspace. Safety of air transportation strongly depends on the performance of on-board positioning sensors. Positioning by data from navigational aids is considered by international aviation community as one of the main stand-by positioning approaches onboard of civil airplanes. However, only positioning by pair of distance measuring equipment (DME) meets requirements of Performance-Based Navigation. A DME service volume model based on path loss between a pair of transmitting and receiving antennas has been proposed in the paper. The model takes into account the influence of relief on radio waves propagation and diffraction from high-altitude elements of relief. The proposed model has been used in the analysis of DME global network performance. In particular, performance of a global network is analyzed based on availability area of DME service, area of positioning by pairs of DME/DME support, availability of particular positioning accuracy, and areas of meeting various RNAV requirements. Obtained results indicate that only in 27.76% of global airspace a DME service can be provided. However, only within 15.9% of airspace, a DME/DME positioning can be used. Results of the analysis indicate about the necessity of actions for further development of global navigational aids network in order to guarantee safe airlines connections around the globe. [ABSTRACT FROM AUTHOR]

Highlights • The problems of quadratic range migration and Doppler frequency migration for the maneuvering target are addressed. • A method based on TSS-FrFT is proposed to achieve the coherent integration and it has superior detection performance and low computational complexity. • The acceleration matched filter is presented to remove the DFRC caused by the sudden change of targets acceleration. Abstract This paper considers the detection problem of radar maneuvering target with the range migration (RM) and Doppler frequency migration (DFM) and proposes an coherent integration method based on two steps scaling and fractional Fourier transform, i.e., TSS-FrFT. To be specific, this method corrects the quadratic RM (QRM) and DFM based on FrFT and a scaling processing of the rotation angle firstly. Then, it eliminates the coupling between the range frequency variable and FrFT domain (FrFD) variable via a second scaling processing. In the end, the coherent integration is achieved by the inverse Fourier transform (IFT) with respect to the range frequency variable. Compared with the existing methods, the proposed TSS-FrFT method has superior detection performance and low computational complexity. Moreover, considering the sudden change of the target acceleration within the coherent integration interval, this paper also presents an acceleration matched filter (AMF) to remove the Doppler frequency rate change (DFRC) caused by this acceleration change. Computer simulation results are also given to demonstrate the effectiveness of the proposed method from different aspects, i.e., computational complexity, coherent integration for a single target and multiple targets and detection performance for a uniform acceleration and non-uniform accelerations. [ABSTRACT FROM AUTHOR]

[Display omitted] • Propose a dual transponder via SINS/USBL tightly coupled method based on range difference. • A measurement timing inconsistency model is proposed to address the reception delay between dual transponder. • The non parametric estimation method kernel density estimation (KDE) is introduced into the maximum correntropy robust algorithm for adaptive estimation of measurement noise. The main factors affecting the positioning accuracy of the Ultra-short base line (USBL) positioning system include sensor errors, marine environment-induced measurement errors, system acoustic array installation errors, and acoustic signal processing errors. These errors include common errors and random noise. The traditional SINS/USBL integrated navigation system models the measurement noise of USBL as random noise while neglecting the treatment of common errors. To solve the above problems, a new dual underwater transponder aided SINS/USBL integrated method is proposed. Firstly, different from the traditional tightly coupled model, a new model based on range difference is proposed to eliminate common errors in underwater acoustic communication, which replaces the traditional range measurement model. Due to slow sound speed and changes in the relative position between the transponder and the carrier, there is inconsistency in the measured arrival time of the dual responder. To solve the problem, a measurement timing inconsistency model is proposed. Secondly, an improved maximum correntropy robust filtering based on kernel density estimation (KDE) is proposed to estimate the characteristics of outliers and improve the adaptability of robust filter to time-varying systems. Finally, simulation and river experiments are conducted. Compared with the traditional tightly coupled method, the dual transponder aided coupled method proposed in this paper can effectively reduce the common errors in signal transmission for USBL and the proposed filter can effectively reduce the impact of complex environment on positioning accuracy. [ABSTRACT FROM AUTHOR]

Highlights • A computationally efficient coherent detection and parameter estimation algorithm via SAF-SFT is proposed. • The proposed algorithm could remove the range cell migration and Doppler spread effects without parameter-searching process. • SAF-SFT method could strike a good balance between computational cost and detection probability as well as the estimation performance. Abstract In this paper, a computationally efficient coherent detection and parameter estimation algorithm via symmetric autocorrelation function (SAF) and scaled Fourier transform (i.e., SAF-SFT) is proposed, involving range cell migration (RCM) and Doppler spread (DS) within the coherent integration (CI) time. In particular, the first SAF and SFT operations are applied to achieve the range and velocity estimations after the generalized keystone transform. With the estimations, the remaining RCM induced by target's velocity could be removed and the target signal could be extracted along the range cell. Then the second SAF and SFT operations are performed on the extracted signal, where the target energy could be coherent integrated and the acceleration estimation can be obtained. Cross term of SAF-SFT is also analyzed and its characteristic indicates the applicability in the scenario of multi-targets. Detailed comparisons of SAF-SFT with several typical algorithms with respect to computational cost, detection probability and parameter estimation ability show that the SAF-SFT could strike a balance between computational cost and detection probability as well as the estimation performance. Simulation results and real test experiment are given to verify the SAF-SFT based approach. [ABSTRACT FROM AUTHOR]

Tour planning represents a challenging task for individuals visiting unfamiliar tourist destinations, mainly due to the availability of numerous attractions (points of interest, POIs) and the complexity of metropolitan public transit networks. Several web and mobile tourist city guides already support personalized tour recommendations. However, they exclusively consider walking tours; namely, they fail in motivating tourists to use public transportation for reaching far located important POIs, thereby compromising the perceived overall attractiveness of recommended tours. In this paper, we introduce eCOMPASS, a context-aware web/mobile application which derives personalized multimodal tours via selected urban attractions. eCOMPASS is the only available research or commercial tour planner that assists the way arounds of tourists through public transit. Far beyond than just providing navigational aid, eCOMPASS incorporates multimodality (i.e. time dependency) within its routing logic aiming at deriving near-optimal sequencing of POIs along recommended tours so as to best utilize the time available for sightseeing and minimize waiting time at transit stops. Further advancing the state of the art, eCOMPASS allows users to define arbitrary start/end locations (e.g. the current location of a mobile user) rather than choosing among a fixed set of locations. Last, eCOMPASS may assist in scheduling lunch breaks at affordable restaurants, conveniently located along the recommended tours. The provision of the above mentioned unique features of eCOMPASS is based on modeling and solving a complex optimization problem which takes into account a long list of problem variables and constraints. This paper describes the routing algorithm which comprises the core functionality of eCOMPASS. Further, it discusses the implementation details of the web and mobile eCOMPASS applications using the metropolitan areas of Athens (Greece) and Berlin (Germany) as case studies. Evaluation results report positive user attitude as to the tour planning output with respect to attractiveness, meaningfulness and the overall perceived utility. [ABSTRACT FROM AUTHOR]

Most of the people affected by vision impairments are over 50 years old, which amplifies cognitive impairments and the risk of falling. This paper proposes a mixed reality assistive system to aid the navigation of visually impaired people by using a Smart Walker, audio feedback to provide cues to be followed, and vibratory feedback to indicate obstacles. To validate this system, 24 volunteers participated of three tasks consisting in a combination of a control strategy (Free Roam, Steering-Assisted Navigation, and Virtual Trail) and a path. To evaluate the experiments, task performance metrics and three questionnaires (Quality of Experience, SUS, and NASA-TLX) were assessed. According to SUS, all control strategies scored above 70, indicating their acceptability. Analyzing and comparing the questionnaires results and the strategies used, the Steering-Assisted Navigation, in which the volunteers had to follow a path indicated only by the haptic feedback provided by the controller, was the most physically and mentally demanding. The other two strategies required less effort, physical, and mental demand. Despite requiring different cognitive loads for navigation, all control strategies combined with the multimodal sensory feedback guided the volunteers during the tasks, evidencing the feasibility of the system. • Development of a mixed reality system to aid the locomotion of the visually impaired. • A Smart Walker provided physical and cognitive assistance. • Audio and vibratory feedback were used to indicate navigation cues, and obstacles. • Three interaction strategies were used to provide different levels of guidance. • Task performance and self-assessment metrics supported this assistive system. [ABSTRACT FROM AUTHOR]

This paper focuses on accomplishing the high reliability reconfigurable FOG signal processing system. Design is done to improve the reliability of the entire system. In order to realize the system reconfigurable, SRAM-based FPGA is adopted as the signal processor. Scrubbing technology based on active partial reconfiguration is used to insure the SRAM-based FPGA operating properly. A 14 MeV neutron radiation experiment is taken to evaluate the radiosensitivity of the system. It is concluded that the design with scrubbing technology as core can increase the reliability significantly. This lies the foundations for the application of high reliability reconfigurable FOG for satellite. [ABSTRACT FROM AUTHOR]

This paper introduces an adaptive interactive multi-model algorithm for the navigation system of the unmanned underwater vehicle (UUV). The underwater environment is diverse and time-varying. Obtaining high-precision navigation is very important for the safety and effectiveness of autonomous navigation of unmanned underwater vehicles, which makes the reliability of UUV navigation-related sensors particularly demanding. When the underwater environment has absorbing substances or a deep-sea environment, the Doppler velocity log (DVL) will produce outliers or even fail. When the vehicle navigates to a flat terrain area and terrain aided navigation (TAN) performs navigation parameter matching, multiple adaptation positions will appear, resulting in abnormal measurement data. Similarly, when UUV sails to a strong magnetic area, magnetic compass (MCP) will be disturbed, etc. To improve the robustness of navigation and reduce the influence of the change of system model and measurement noise model caused by environmental factors, an adaptive interactive multi-model algorithm is proposed, which is carried out with the UUV based INS/DVL/MCP/TAN integrated navigation system. For the problem that the measurement noise of the system changes, different models are organized into a collection, and according to different situations, the corresponding model or hybrid model is selected in the collection of models to describe the measurement noise, so as to realize the seamless switching of the system model. The simulation results show that the adaptive multi-model algorithm can effectively control the impact of system noise model uncertainty on navigation accuracy, so that UUV has higher accuracy and less computation than single navigation and traditional algorithms, and has robustness and scalability. • The overall computational effort during navigation would be too large if the observed models were completely covered. • The noise estimation unit is accessed at the front end of the interactive multi-model algorithm to estimate the observation noise covariance matrix at this time, and the set of observation models is built around this value to reduce the number of models covering all system states, thus reducing the computational effort. [ABSTRACT FROM AUTHOR]

It is extremely challenging to carry out an advanced adaptive navigation system in the complex environment of a port. Especially in the waters that are about to be berthed, the unmanned surface vehicles (USVs) should autonomously identify and avoid dense buoys according to the rules. Each country has corresponding mandatory documents that strictly regulate the shape, color and orientation of water buoys in coastal and estuary channels. Aiming at the problem of USV collision avoidance navigation under the constraints of the IALA (International Association of Marine Aids and Lighthouse Authorities) Maritime buoyage system, this paper designs a mixed environment model including multiple ocean buoys according to this rule. By using the deep neural network to extract the state features of the target, and setting the reward function reasonably, the USV can not only navigate to the target autonomously, but also identify the corresponding buoy and give the corresponding decision. Using different DQN optimization algorithms to conduct comparative experiments, the stability of the algorithm's learning of the optimal strategy is improved. The results show that the algorithm can accurately avoid obstacles ahead, identify buoys effectively, and realize effective autonomous collision avoidance decision-making in complex environments with static obstacles and buoys with indicating function. This research can provide theoretical basis and method reference for USV's autonomous navigation in port. • Through the in-depth analysis of the IALA Maritime Buoyage System, the rule information of each navigation aid is designed and embedded into the environment definition. • For autonomous navigation and collision avoidance decision-making, the reward function is optimized and a deep reinforcement learning-based USV autonomous navigation decision-making algorithm is proposed. • By using the three variant algorithms of Q-Learning to conduct comparative experiments, the problems that autonomous navigation decision-making algorithms tend to fall into local optimal solutions and low iterative efficiency are solved. • The simulation results based on pytorch and Unity3d show that USV can finally judge whether its behavior violates the IALA Buoyage System. And the navigation task can also be successfully completed at the new initial point. [ABSTRACT FROM AUTHOR]

• A percussion acoustic signal denoising method in marine environment is proposed. • Compared with other denoising methods, the proposed method can significantly improve the SNR of noisy percussion acoustic signals under the complex marine environment with noise interference. • When the main peak frequency of the denoised percussion acoustic signal with the proposed method is used for damage identification, the error is only about 3% Percussion-based inspection of structures has attracted widespread attention in recent years. However, the percussion acoustic signals collected in the marine environment usually have a low signal-to-noise ratio (SNR) and are difficult to use directly due to the interference by a multitude of marine noises. The frequency contents of the ambient noises usually overlap with those of the percussion acoustic signals, thus limiting the denoising using traditional methods. This paper proposes a denoising method using the least mean square (LMS) algorithm to obtain the approximate percussion signal. The noisy percussion signals and marine noise are recorded synchronously by two hydrophones. Then the LMS algorithm processes the collected signals and provides the frequency peaks that cannot be extracted with conventional methods. The proposed method is validated by experiments conducted in a noiseless laboratory environment and a noisy, naturally occurring marine environment. The results reveal that the proposed method is excellent in denoising the raw signal, and the error is about 3% in terms of differences in the estimated value of the primary peak frequency. This study demonstrates the broad potential for the method to be applied toward damage detection for underwater structures. [ABSTRACT FROM AUTHOR]

Abstract: The automatic extraction of objects from laser scans and images has been a topic of research for decades. Nowadays, with new services expected, especially in the area of navigation systems, location based services, and augmented reality, the need for automated, efficient extraction systems becomes more urgent than ever. This paper reviews a number of automatic and semi-automatic reconstruction methods in more detail in order to reveal their underlying principles. It then discusses some general properties of reconstruction approaches which have evolved. This shows that, although research is still far from the goal of the initially envisioned fully automatic reconstruction systems, there is now a much better understanding of the problem and the ways it can be tackled. [Copyright &y& Elsevier]

This paper proposes a novel 3D pantograph reconstruction method for the visualization and inspection based on the single-view scanned data and prior Computer-Aided Design (CAD) model. The proposed method uses the point cloud to reconstruct a scanned surface by the fusion of the point cloud and prior CAD surface. Then, a 3D model is reconstructed by integrating the scanned surface and the CAD model through an edge reconstruction process. Finally, the pantograph is inspected by the deviation analysis. The proposed method is validated by the pantograph data collected in a locomotive workshop with line structured light scanning measurement technology. Compared with the state-of-the-art methods, the proposed method can reconstruct the complete 3D model with high accuracy. Furthermore, the reconstructed 3D model has been successfully applied to the anomaly detection and visualization in the pantograph inspection, which is of great significance for improving the pantograph inspection efficiency and reducing traffic accidents. • A 3D pantograph reconstruction method is proposed for visualization and inspection. • A non-hole surface reconstruction method is proposed based on CAD mesh densification. • The 3D visualization can improve the efficiency of the pantograph maintenance. [ABSTRACT FROM AUTHOR]

This paper deals with the adaptive sliding mode fault-tolerant control problem for unmanned marine vehicles (UMVs) with signal quantization and state time-delay. A unified thruster fault model for UMVs is built by taking bias, partial, total, time-varying stuck, and hard-over faults into account. For UMVs in the network environment, the effects of quantization and state time-delay on UMVs are inevitable. In this situation, adaptive sliding mode technology and dynamic quantization parameter adjustment strategy are combined to compensate for the quantization errors and time-delay effects. Compared with the traditional method, a larger quantization parameter adjustment range is given and a new dynamic quantization parameter adjustment strategy is designed. Further the quantized sliding mode fault-tolerant controller independent of fault detection and diagnosis mechanism is designed for UMVs in the presence of time-delay and various thruster faults to reduce the oscillation amplitudes of the yaw velocity error. The comparison simulations of a typical floating production ship have been provided to demonstrate the effectiveness of the proposed algorithm. • A unified thruster fault model is established. • Thruster fault factors and time-delay parameters are taken into account in the quantization parameter adjustment strategy. • A larger quantization parameter adjustment range is given. [ABSTRACT FROM AUTHOR]

Abstract: The main aim of this work is to derive a correct formulation for the characteristic resistance of a mooring line segment with lognormally distributed component resistances and substitute an equation proposed by Vazquez-Hernandez et al. [Vazquez-Hernandez AO, Ellwanger GB, Sagrilo LVS. Reliability-based comparative study for mooring lines design criteria. Appl Ocean Res 2006; 28(6):398–406] in a paper published in this journal, which is not correct. The mooring line is considered as a series system and the resistances of individual components of a line segment are statistically independent and identically distributed; furthermore, the case of normally distributed component resistances is also discussed. A comparison with the corresponding equation proposed by DNV-OS-E301 is given. Results show that the formula proposed by Vazquez-Hernandez et al. [Vazquez-Hernandez AO, Ellwanger GB, Sagrilo LVS. Reliability-based comparative study for mooring lines design criteria. Appl Ocean Res 2006; 28(6):398–406] overestimates quite significantly the characteristic resistance of a mooring line segment. [Copyright &y& Elsevier]