Every sailor, at the back of his or her mind, is aware that the nearest land is likely to be directly beneath the ship's keel and he or she is interested to know just how near. For over two thousand years, mariners measured depth of water by using a sounding rod in shallow areas and the lead and line in deeper water. This paper considers how, during the “Dark Ages”, sailors in the North Sea might have navigated, including the use of sounding rods and lead lines for way-finding during a time when no other navigational instruments were available. Because of the lack of contemporary records the authors firstly consider the use of depth finding in earlier and later times to shed light on how the early North Sea sailors might have operated. The latter part of this paper takes account of the earlier discussion, together with some records of North Sea voyaging, to suggest how “Dark Age” sailors might have used sounding rods, the lead and line, and other techniques to navigate around and across the North Sea.

In this study, we develop a Multi-constellation Global Navigation Satellite System (GNSS) Receiver Differential Code Bias (MGR-DCB) model. The model estimates the receiver DCBs for the Global Positioning System (GPS), BeiDou and Galileo signals from the ionosphere-corrected geometry-free linear combinations of the code observations. In order to account for the ionospheric delay, a Regional Ionospheric Model (RIM) over Europe is developed. GPS observations from 60 International GNSS Servoce (IGS) and EUREF reference stations are processed in the Bernese-5·2 Precise Point Positioning (PPP) module to estimate the Vertical Total Electron Content (VTEC). The RIM has spatial and temporal resolutions of 1° × 1° and 15 minutes, respectively. The receiver DCBs for three stations from the International GNSS Service Multi-GNSS Experiment (IGS-MGEX) are estimated for three different days. The estimated DCBs are compared with the MGEX published values. The results show agreement with the MGEX values with mean difference and Root Mean Square Error (RMSE) values less than 1 ns. In addition, the combined GPS, BeiDou and Galileo VTEC values are evaluated and compared with the IGS Global Ionospheric Maps (IGS-GIM) counterparts. The results show agreement with the GIM values with mean difference and RMSE values less than 1 Total Electron Content Unit (TECU).

This paper is the second part of a two-part research effort to find the optimal detector and estimator that minimise the integrity risk in Receiver Autonomous Integrity Monitoring (RAIM). Part 1 shows that for realistic navigation requirements, the solution separation RAIM method can approach the optimal detection region when using a least-squares estimator. This paper constitutes Part 2. It presents new methods to design Non-Least-Squares (NLS) estimators, which, in exchange for a slight increase in nominal positioning error, can substantially lower the integrity risk. A first method is formulated as a multi-dimensional minimisation problem, which directly minimises integrity risk, but can only be solved using a time-consuming iterative process. Parity space representations are then exploited to develop a computationally-efficient, near-optimal NLS-estimator-design method. Performance analyses for an example multi-constellation Advanced RAIM (ARAIM) application show that this new method enables significant integrity risk reduction in real-time implementations where computational resources are limited.

Facilitated by recent establishment of terrestrial networks and satellite constellations of Automatic Identification System (AIS) receivers, ship trajectories are becoming increasingly available and the size of recorded trajectories is getting larger. Large sets of trajectories create problems of storing, transmitting and processing data. Using appropriate methods, an accurate representation of the original trajectories can be obtained by compressing redundant information, while maintaining the main characteristic elements. In this paper, a new scheme and the implementation of the Douglas-Peucker (DP) algorithm are presented, which can simplify AIS trajectories by extracting characteristic points. As for the simplification threshold, the solo parameter of the DP algorithm, a new AIS-based minimum ship domain evaluation method is proposed and acts as criteria for simplification threshold determination. Finally, a validation is made to examine the effectiveness of the DP simplification algorithm and the rationality of the simplification threshold. The result indicates that the DP algorithm can simplify AIS trajectories effectively; the simplification threshold is scientific and reasonable.

Numerous applications, not only Earth-based, but also space-based, have strengthened the interest of the international scientific community in using Global Navigation Satellite Systems (GNSSs) as navigation systems for space missions that require good accuracy and low operating costs. Indeed, already successfully used in Low Earth Orbits (LEOs), GNSS-based navigation systems can maximise the autonomy of a spacecraft while reducing the burden and the costs of ground operations. That is why GNSS is also attractive for applications in higher Earth orbits up to the Moon, such as in Moon Transfer Orbits (MTOs). However, the higher the altitude the receiver is above the GNSS constellations, the poorer and the weaker are the relative geometry and the received signal powers, respectively, leading to a significant navigation accuracy reduction. In order to improve the achievable GNSS performance in MTOs, we consider in this paper an adaptive orbital filter that fuses the GNSS observations with an orbital forces model. Simulation results show a navigation accuracy significantly higher than that attainable individually by a standalone GNSS receiver or by means of a pure orbital propagation.

The Faculty of Maritime Studies, University of Rijeka, Croatia, manages the European Union (EU) project “Avoiding Collisions at Sea” (ACTs). The project is funded by the European programme “Leonardo da Vinci”. Other maritime education and training institutions participating in this project come from Great Britain, Spain, Slovenia, Bulgaria and Turkey. The purpose of this research was to identify skill gaps in knowledge and teaching of COLREGs (International Regulations for Preventing Collisions at Sea 1972 - Rules) for nautical Bachelor of Science (BSc) students and experienced deck officers. The analysis of the research on marine accidents has identified vessel collisions as one of the most frequent types of accidents. Further research showed that human error and misinterpretation of the Rules are the most frequent reasons for vessel collisions. Using a questionnaire, nautical students/navigating cadets and navigating officers' understanding of the Rules was tested. The results showed skill gaps in understanding of some parts of the COLREGs due to wrong interpretation and application of the Rules. The authors claim that it is possible to improve the professional competence of navigating officers by applying proper learning methods using real-life scenarios and e-learning.

Advances in technological innovation have been deployed to support autonomous or semi-autonomous vehicles in many industries. A question that remains unanswered is why very little progress has been made in remote pilotage over the past 15 years. This paper draws together theories from innovation management and the high reliability organisation literatures to shed light on this question. Using a case study of two Australian ports, we examine a business case for remote pilotage demonstrating that despite positive cost benefit models, ambiguities in benefits exist throughout the ecosystem. The discussion sheds light on unique challenges that port executives face where it is necessary to simultaneously develop a strategy to: (1) manage the internal innovation process, and (2) manage the external consequences of the innovation by mobilising allies, managing opponents, and converting those who are indifferent to the innovation. The main contribution of this paper is to show that any assessment of the innovation challenge facing remote pilotage and enhanced navigational assistance requires the maritime industry to ask new questions not previously considered.

The Delay Locked Loop (DLL) tracking algorithm is one of the most widely used in GPS receivers. It uses different correlators such as the Early-Late Slope (ELS) correlator and High-Resolution Correlator (HRC) to mitigate code phase multipath. These techniques are effective for weak multipath environments but they may not be suitable for challenging multipath environments. The Multipath Estimating Delay Lock Loop (MEDLL) shows better performance than the classical methods. However, MEDLL still has limited capabilities in severe multipath environments. This paper introduces a robust multipath mitigation technique based on fast orthogonal search to obtain better delay estimation for GPS receivers. This research utilised a SPIRENT Global Navigation Satellite Systems (GNSS) simulator to compare the performance of the proposed method with other multipath mitigation techniques. Experimental results demonstrated that the performance of the proposed algorithm was better than the classical and advanced techniques under the multipath scenarios tested.

Nautical services should be allocated efficiently as they have great resource costs. In this paper, the Marine Pilotage Service in the Istanbul Strait has been analysed by using Rockwell Arena Simulation Software. The purpose of the study is to find the required number of marine pilots for vessel traffic flow in the Istanbul Strait. It is evaluated thoroughly by a stochastic, dynamic, discrete simulation for safe service standards in pilotage. The result of the paper shows that discrete simulation technique is an efficient and reliable way of solving complex techno-nautical service allocation problems as proven by experts. As the discrete simulation result data shows, most other techno-nautical services can also be modelled and optimised by using similar techniques. Areas like optimisation of the number of pilots, tugs, resource allocation problems, berthing area selections and many more complex and inherently stochastic problems can be reliably solved by simulation experiments.

A planet centroid is an important observable object in autonomous optical navigation. A high-accuracy algorithm is presented to extract the planet centroid from its raw image. First, we proposed a planet segmentation algorithm to segment the planet image block to eliminate noise and to reduce the computation load. Second, we developed an effective algorithm based on Prewitt-Zernike moments to detect sub-pixel real edges by determining possible edges with the Prewitt operator, removing pseudo-edges in backlit shady areas, and relocating real edges to a sub-pixel accuracy in the Zernike moments. Third, we proposed an elliptical model to fit sub-pixel edge points. Finally, we verified the performance of this algorithm against real images from the Cassini-Huygens mission and against synthetic simulated images. Simulation results showed that the accuracy of the planet centroid is up to 0·3 pixels and that of the line-of-sight vector is at 2·1 × 10−5 rad.

This paper proposes a Radio Frequency Identification (RFID)/ in-vehicle sensors fusion strategy for vehicle positioning in completely Global Positioning System (GPS)-denied environments such as tunnels. The strategy employs a two-step approach, namely, the calculation of the distances between the RFID tags and the reader, and then the global fusion estimation of vehicle position. First, a Least Square Support Vector Machine (LSSVM) algorithm is developed to obtain distance. Next a novel Federated Unscented Kalman Filter (FUKF) is designed to realise the global fusion. The decentralised federated filter is adopted to combine the data from RFID and in-vehicle sensors, and the UKF is employed to design a local filter since it has better ability to deal with a nonlinear problem than an Extended Kalman Filter (EKF). Due to the optimised layout of RFID tags and the application of the decentralised filter, the number of tags is reduced. Finally, the feasibility and effectiveness of the proposed strategy are evaluated through experiments.

Accurate velocity estimates are critical in highly dynamic positioning, airborne gravimetry, and geophysics applications. This paper focuses on the evaluation of the performance of velocity estimation using the BeiDou navigation satellite system (BDS) alone and integrated Global Positioning System (GPS)/BDS. Firstly, we analyse and compare the position-derivation method and analytical method which are used to calculate BDS satellite velocity from broadcast ephemeris. Results show that the accuracy of the estimated velocity by position-derivation method can be within 1 mm/s and better than that of the analytical method. Secondly, velocity estimation tests were carried out both in static and kinematic modes. The results show that: 1) the accuracy of BDS velocity estimation is in the same order of magnitude to that of GPS; 2) Compared with a single navigation system, the stability and accuracy of velocity estimation can be remarkably improved by integrated GPS/BDS, especially under conditions of poor observation; 3) Compared with Helmert variance component estimation, it is more appropriate and efficient to assign the weights of different types of observations using equivalent weight ratio. Finally, the ionospheric influence on velocity estimation with single-frequency observations can reach several mm/s; this influence can be significantly mitigated by using ionosphere-free combination observations.

The Global Positioning System (GPS) has become widespread in many civilian applications. GPS signals are vulnerable to interference and even low-power interference can easily spoof GPS receivers. In this paper, two techniques are proposed based on correlators and adaptive filtering to diminish the effect of spoofing on GPS-based positioning. The suggested algorithms are implemented in the tracking loop of the receiver. As a first method, a high-resolution correlator is utilised to avoid big parts of the influence of interference. To improve the results, a multicorrelator technique is also employed. In the second method, an adaptive filter is used for estimating the parameters of authentic plus spoof signals. Interference elimination is performed by subtracting the estimated conflict effects from the measured correlation function. These techniques provide easy-to-implement quality assurance tools for anti-spoofing. As a primary step, in this article, the proposed algorithms have been implemented in a Software Receiver (SR) to prove the concept of idea in multipath-free environments.

For the integrated navigation system, the correctness and the rapidity of fault detection for each sensor subsystem affects the accuracy of navigation. In this paper, a novel fault detection method for navigation systems is proposed based on Gaussian Process Regression (GPR). A GPR model is first used to predict the innovation of a Kalman filter. To avoid local optimisation, particle swarm optimisation is adopted to find the optimal hyper-parameters for the GPR model. The Fault Detection Function (FDF), which has an obvious jump in value when a fault occurs, is composed of the predicted innovation, the actual innovation of the Kalman filter and their variance. The fault can be detected by comparing the FDF value with a predefined threshold. In order to verify its validity, the proposed method is used in a SINS/GPS/Odometer integrated navigation system. The comparison experiments confirm that the proposed method can detect a gradual fault more quickly compared with the residual chi-squared test. Thus the navigation system with the proposed method gives more accurate outputs and its reliability is greatly improved.