Map-matching is widely used in automotive navigation systems to locate vehicle positions on a given digital road map. Various map-matching algorithms have been developed focusing on different application needs. Within the Ghosthunter project, a weighting-function-based map-matching algorithm has been developed for detecting wrong-way driving in order to improve road safety, particularly in Autobahn entrance and exit areas. This paper aims at exploring the potential use of lane-level attributes and height data in improving the success rate of the previously presented algorithm. This algorithm performs well in entrance and exit areas to the Autobahn, with a high success rate of 99.5% in identifying the road on which the vehicle is actually travelling. In the enhanced algorithm presented in this paper the weight coefficients used for computing the total weighting score of candidate roads are adjusted with the aid of one or both kinds of these precise data. The results confirmed that the usage of these precise data can effectively help to detect and correct mismatches at junctions and overpasses.

Safety in ice-covered polar waters can be optimised via the choice of a ship's route. This is of utmost importance for conventional as well as autonomous ships. However, the current state of the art in e-Navigation tools has left two open questions. First, what essential information are these tools still missing, and second, how they are seen by sea captains. In order to address these questions, we organised an ice navigation workshop to systematically collect routing justifications given by and waypoints planned by experienced sea captains that are particularly seasoned in ice navigation. Here, we report the outcome of that workshop. Our key findings include the reasoning and the commentary of the participants in looking for a better and safer route. These comments shed light upon both the official and unofficial code of conduct in open waters and boil down into a list of additional prerequisite information if further steps towards system autonomy are sought. Finally, the expert-planned waypoints are to be published alongside this paper to act as a benchmark for future maritime studies.

Navigation methods, traditional and modern, use lines of position in the plane. Standard Gaussian assumptions about errors leads to a constant sum of squared distances from the lines defining a probability contour. It is well known these contours are a family of ellipses centred on the most probable position and they can be computed using algebraic methods. In this paper we show how the most probable position, the axes and foci of ellipses can be found using geometric methods. This results in a ruler and compasses construction of these points and this gives insight into the way the shape and orientation of the probability contours depend on the angles between the lines of position. We start with the classical case of three lines of position with equal variances, we show how this can be extended to the case where the variances in the errors in the lines of position differ, and we go on to consider the case of four lines of position using a methodology that generalises to an arbitrary number of lines.

The Iterated Closest Contour Point (ICCP) algorithm is widely used in geomagnetic navigation. In order to enhance the anti-interference performance of the ICCP, an improved algorithm is proposed. First, the principle of delta modulation is introduced to generate a geomagnetic matching sequence according to the magnetic fluctuations, this assists finding the optimal quantitative step and matching length; thus, the algorithm's accuracy and real-time performance are improved. Second, in order to solve the problem of geomagnetic matching under an interference environment, a Probability Data Association (PDA) algorithm based on regenerated measurements is adopted. The ideal magnetic value is regarded as a target, and the measured values within the confidence region are taken as the effective measurements of the target. Each of them will give an estimation of the vehicle's position. Considering the constraints of a vehicle's kinematic performance, its final position can be obtained by fusing all effective estimations with the PDA algorithm. Simulation and semi-physical experiments have verified the feasibility and effectiveness of the proposed algorithm. The Regenerated Measurements (RM)-PDA algorithm shows better performance and can be used in practical applications.

In this study, the effect of acceleration matching according to sensor specifications in rapid transfer alignment is analysed. In general, the velocity and attitude information of the Master Inertial Navigation System (MINS) is used for transfer alignment. MINS angular velocity information is used to improve the alignment speed in shipboard transfer alignment. Acceleration matching, on the other hand, is generally considered an impractical option for transfer alignment. However, in the case of shipboard transfer alignment, acceleration matching is thought to be effective. In order to analyse the performance of acceleration matching, a performance index is defined and the efficiency of acceleration matching is analysed according to various sensor specifications and simulation environments. Based on the analysis of the estimated performance according to the simulation results, it is confirmed that acceleration matching in rapid transfer alignment is valid.

The objective of this study is to propose a methodology for assessing waterway traffic capacity in the Shanghai estuary of the Yangtze River. To achieve this objective, we first put forward the estimation method which utilises the minimum collision distance taking the dynamic ship domain into consideration. Considering possible effects caused by unknown external factors, the waterway traffic capacity is then represented by a probability distribution. Finally, we quantify the equivalent units of ships with various ship sizes as well as the effects of large-sized ships on the waterway traffic capacity. Results show that a large-sized ship is equivalent to more small-sized ships during the daytime period than at night. In addition, the deployment of large-sized ships could increase the waterway traffic capacity and such an increment highly depends on the increased proportion of large-sized ships in the waterway traffic.

The geometric distribution of navigational aids is one of the most important elements to be taken into account in the planning of maritime terrestrial navigation systems. It determines to a large extent the capability of vessels to obtain high-precision position coordinates. Therefore, the optimisation of their location is a key element at the planning stage, in particular on port approach fairways. This article attempts to use computer simulation methods to assess the positioning accuracy of a vessel that follows a constant course and speed on a port approach fairway. The analysis uses a technique based on the Extended Kalman Filter (EKF) Two-Dimensional (2D) Range-Bearing Simultaneous Location and Mapping (SLAM) method. In the simulation experiment conducted, the research object determined its position based on bearing and distance to fixed position beacons, which changed their locations in subsequent passages of the vessel. A geometrically optimal configuration of the terrestrial navigation marking system guaranteeing the highest positioning accuracy was identified as a result of the deliberations. The study analysed more than 20,000 cases of different configurations (locations) of the fixed position beacons, demonstrating that the adopted algorithm can be used successfully in the planning of their deployment in the context of ensuring minimum accuracy requirements for the positioning of navigational signs on port approach fairways and under restricted conditions by navigational marking services, as set out in International Maritime Organization (IMO) Resolutions A915 (21) and A953(22).

Real multi-Autonomous Underwater Vehicle (AUV) cooperative systems operate in complicated marine environments. The interaction between a multi-AUV cooperative system and its marine environment will affect the reliability of the system. Current is an important influencing factor of multi-AUV cooperative systems. A reliability index of multi-AUV cooperative systems known as System Reliable Probability (SRP) is proposed in this study. A method to calculate SRP is introduced, and the influence of current on SRP is discussed in detail. Current is considered an attack source, and the degree of its influence on SRP is calculated. As an example, the performance of this method is shown on two multi-AUV cooperative systems. Results show that the influence of the same current environment on different structures of the multi-AUV cooperative systems differs. This result provides a reference for the structure selection of multi-AUV systems. This study provides a practical method to estimate the reliability of multi-AUV cooperative systems.

Both the code–phase combination and the Geometry-Free (GF) phase combination are widely employed to detect and repair cycle slips for BeiDou Navigation Satellite System (BDS) triple-frequency observations. However, the effect of residual ionospheric delay on Narrow-Lane (NL) or GF observations must be considered to avoid incorrect cycle–slip estimation. To improve the accuracy in repairing cycle slips, a corrective ionospheric delay value predicted from the previous ionosphere sequence is used to amend the NL or GF observations at the current epoch. The main purpose of the work reported here is to evaluate the efficacy of a three-step method proposed to detect and repair cycle slip using two extra-wide-lane code–phase and one GF phase combination observations. BDS triple-frequency data were processed in two stages: separate processing of geosynchronous Earth orbit satellites, and the division of inclined geosynchronous satellite orbit and medium Earth orbit satellites into two groups for processing at 30° elevation thresholds. Results revealed that using the prediction models to correct NL or GF observations could ensure a rounding success rate of cycle slip close to 100%, even under high ionospheric activity.

In this paper, a new scene recognition visual descriptor called Enhanced Scale Invariant Feature Transform-based Sparse coding Spatial Pyramid Matching (Enhanced SIFT-ScSPM) descriptor is proposed by combining a Bag of Words (BOW)-based visual descriptor (SIFT-ScSPM) and Gist-based descriptors (Enhanced Gist-Enhanced multichannel Gist (Enhanced mGist)). Indoor scene classification is carried out by multi-class linear and non-linear Support Vector Machine (SVM) classifiers. Feature extraction methodology and critical review of several visual descriptors used for indoor scene recognition in terms of experimental perspectives have been discussed in this paper. An empirical study is conducted on the Massachusetts Institute of Technology (MIT) 67 indoor scene classification data set and assessed the classification accuracy of state-of-the-art visual descriptors and the proposed Enhanced mGist, Speeded Up Robust Features-Spatial Pyramid Matching (SURF-SPM) and Enhanced SIFT-ScSPM visual descriptors. Experimental results show that the proposed Enhanced SIFT-ScSPM visual descriptor performs better with higher classification rate, precision, recall and area under the Receiver Operating Characteristic (ROC) curve values with respect to the state-of-the-art and the proposed Enhanced mGist and SURF-SPM visual descriptors.

Although topographic mapping missions and geological surveys carried out by Autonomous Underwater Vehicles (AUVs) are becoming increasingly prevalent, the lack of precise navigation in these scenarios still limits their application. This paper deals with the problems of long-term underwater navigation for AUVs and provides new mapping techniques by developing a Bathymetric Simultaneous Localisation And Mapping (BSLAM) method based on graph SLAM technology. To considerably reduce the calculation cost, the trajectory of the AUV is divided into various submaps based on Differences of Normals (DoN). Loop closures between submaps are obtained by terrain matching; meanwhile, maximum likelihood terrain estimation is also introduced to build weak data association within the submap. Assisted by one weight voting method for loop closures, the global and local trajectory corrections work together to provide an accurate navigation solution for AUVs with weak data association and inaccurate loop closures. The viability, accuracy and real-time performance of the proposed algorithm are verified with data collected onboard, including an 8 km planned track recorded at a speed of 4 knots in Qingdao, China.

This paper introduces a scheme for waypoint-based path-following control for an Unmanned Robot Sailboat (URS) in the presence of actuator gain uncertainty and unknown environment disturbances. The proposed scheme has two components: intelligent guidance and an adaptive neural controller. Considering upwind and downwind navigation, an improved version of the integral Line-Of-Sight (LOS) guidance principle is developed to generate the appropriate heading reference for a URS. Associated with the integral LOS guidance law, a robust adaptive algorithm is proposed for a URS using Radial Basic Function Neural Networks (RBF-NNs) and a robust neural damping technique. In order to achieve a robust neural damping technique, one single adaptive parameter must be updated online to stabilise the effect of the gain uncertainty and the external disturbance. To ensure Semi-Global Uniform Ultimate Bounded (SGUUB) stability, the Lyapunov theory has been employed. Two simulated experiments have been conducted to illustrate that the control effects can achieve a satisfactory performance.

The Strait of Istanbul is one of the world's busiest, narrowest and most winding waterways. As such, there is a high grounding probability for vessels. Although a number of grounding probability models exist, they have been deemed unsuitable by local maritime experts, due to their insufficient stopping distance criteria for narrow waterways. Thus, there is a need for a new model. This paper proposes a two-component grounding probability model that multiplies the geometric grounding probability (calculated with a kinematic-based model) with the causation probability (calculated with a specially designed Bayesian network). The geometric probability model is improved in terms of stopping distance parameters and the Bayesian network is crafted for narrow waterways. The model is then deployed with pre-determined parameters within the Strait of Istanbul to run risk analysis scenarios. The results, validated with actual grounding records, show that the causation probability is the key component for quantifying the probability of grounding in narrow waterways. If navigated without frequent evasive manoeuvres, grounding would be almost inevitable. Although this study focuses on the Strait of Istanbul, the proposed approach can be applied to research into grounding probability of vessels navigating through other waterways.

Alarm fatigue is a critical safety issue, as it can increase workload and impair operators' situational awareness. This paper proposes a design methodology to enhance the interaction between alarm systems and operators. Through input from VTS personnel as the fundamental design requirements, a user requirement-driven design framework is proposed. It integrates quality function deployment, the theory of inventive problem solving, and software quality characteristics into three design phases. In Phase I, user requirements are obtained from the analysis of current working processes. Phase II investigates the specific non-functional design requirements of vessel alarm systems and the contradictions. In Phase III, the innovative principles generated with the contradiction matrix were analysed. A case study was conducted to verify and illustrate this framework, resulting in a conceptualisation design of a smart vessel alarm system.

Considering that traditional visual navigation cannot be utilised in low illumination and sparse feature environments, a novel visual-inertial integrated navigation method using a Structured Light Visual (SLV) sensor for Micro Aerial Vehicles (MAVs) is proposed in this paper. First, the measurement model based on an SLV sensor is studied and built. Then, using the state model based on error equations of an Inertial Navigation System (INS), the measurement model based on the error of the relative motion measured by INS and SLV is built. Considering that the measurements in this paper are mainly related to the position and attitude information of the present moment, the state error accumulation in traditional visual-inertial navigation can be avoided. An Adaptive Sage-Husa Kalman Filter (ASHKF) based on multiple weighting factors is proposed and designed to make full use of the SLV measurements. The results of the simulation and the experiment based on real flight data indicate that high accuracy position and attitude estimations can be obtained with the help of the algorithm proposed in this paper.

In traditional Simultaneous Localisation and Mapping (SLAM) algorithms based on Extended Kalman Filtering (EKF-SLAM), the uncertainty of state estimation will increase rapidly with the development of the exploration process and the increase of map area. Likewise, the computational complexity of the EKF-SLAM is proportional to the square of the number of feature points contained in the state variables in a single filtering process. A new SLAM algorithm combining the local submaps and the body-fixed coordinates of the rover is presented in this paper. The algorithm can reduce the computational complexity and enhance computational speed in consideration of the processing capability of the onboard computer. Due to the introduction of local submaps, the algorithm represented in this paper is able to reduce the number of feature points contained in the state variables in each single filtering process. Therefore, the algorithm could reduce the computational complexity and improve the computational speed. In addition, rover body-fixed SLAM could improve the navigation accuracy of a rover and decrease the cumulative linearization error by coordinates transformation during the update process, which is shown in the simulation results.

The Very High Frequency (VHF) Data Exchange System (VDES) is a new radio communication system being developed by the international maritime community, with the principal objectives to safeguard existing Automatic Identification System (AIS) core functions and enhance maritime communication applications, based on robust, efficient and secure data transmission with wider bandwidth than the AIS. VDES is also being considered as a potential component of the R-mode concept, where the same signals used for communication are also used for ranging, thus mitigating the impact of disruptions to satellite positioning services. This paper establishes statistical performance bounds on the ranging precision of VDES R-mode, assuming an additive white Gaussian noise propagation channel. Modified Cramér-Rao bounds on the pseudorange estimation error are provided for all waveforms currently proposed for use in terrestrial VDES communications. These are then used to estimate the maximum usable ranges for AIS/VDES R-mode stations. The results show that, under the assumed channel conditions, all of the new VDES waveforms provide better ranging performance than the AIS waveform, with the best performance being achieved using the 100 kHz bandwidth terrestrial VDE waveforms.

People with physical disabilities often face many challenges due to the non-compliance of public buildings to accessibility standards. Hence, it is necessary to provide them with relevant information about the quality of access associated with the environment they plan to visit. In this paper, we propose ‘AccessVOR’ (Accessibility assessment based on VORonoï Diagram), a novel approach that aims to automatically generate an indoor navigation network and to assess its accessibility for people moving with wheelchairs based on the American with Disabilities Act Accessibility Guidelines (ADAAG). A semantically enriched spatial database is developed based on ADAAG and the Indoor Geography Markup Language (IndoorGML) standard. A Three-Dimensional (3D) navigation-graph is then generated from the various components of an indoor environment using a Voronoï Diagram. The semantics of ADAAG allow assessing the accessibility of each segment of this navigation graph. Next, a navigation cost is allocated to this graph based on the accessibility of each segment of the network graph for navigation purposes.

A robust adaptive nonlinear asymptotic regulating control law is designed for dynamically positioned vessels exposed to unknown time-varying external disturbances incorporating Fuzzy Logic Systems (FLSs), projection operators, and the “robustifying” term into the vectorial backstepping technique. The FLSs approximate the vessel unknown dynamics and the update laws based on the online projection operators update the fuzzy weight vectors. The robustifying term handles the external disturbances and the fuzzy approximation errors. The designed Dynamic Positioning (DP) control law achieves asymptotic regulation of the vessel's position and heading and makes the other signals in the DP closed-loop control system of vessels be uniformly ultimately bounded. Simulations based on the Marine System Simulator toolbox validate the designed DP control law.