Maritime navigation is a complex task involving the acquisition, analysis, and interpretation of information using seamanship, professional knowledge, and technology. As the maritime industry transitions towards maritime autonomous surface ships (MASS), there is an increasing gap between the operator and the technology. This paper explores a collision avoidance decision support system for navigation from the navigator's perspective. The system, developed by Wärtsilä, is called Advanced Intelligent Manoeuvring (AIM) and can generate suggestions for course or speed alterations based on data from surrounding traffic. Nineteen Swedish navigators completed three ship traffic scenarios with and without decision support. Qualitative data were collected using interviews and analysed with thematic analysis. The results show that the participants perceive the decision support system as an advisory tool to visualise how traffic situations could unfold, a task currently difficult for most navigators. This paper discusses the present and near future of maritime navigation, highlighting the benefits of automation, while remaining vigilant about the potential dangers.

This paper reports the development of a DGPS navigation system integrated with altitude aiding. In this system, a digital height dataset is used for altitude augmentation. A two-dimensional (2-D) positioning algorithm is discussed and modified based on previous publications. The developed algorithm was implemented on the Brunel Inverse DGPS system. The performance of the new developed system is experimentally verified and compared with three-dimensional (3-D) GPS and DGPS systems. The experimental results showed 86% availability of positioning services; whereas for the 3-D GPS system alone, the availability was only 63% of time. In addition, the accuracy of the system was improved from 7.1 to 6.1 m (RMS) for GPS and from 6.0 to 5.1 m (RMS) for DGPS when compared to standalone 3-D modes.

The next generation Global Navigation Satellite Systems (GNSS), such as Galileo and Global Positioning System (GPS) modernization, will use signals with equal code and bit periods, resulting in a potential bit sign transition in each primary code period of the received signal segments. A bit sign transition occurring within an integration period usually causes a splitting of the Cross Ambiguity Function (CAF) main peak into two smaller side lobes along the Doppler shift axis in the search space and it may lead to an incorrect Doppler shift estimate, which results in a serious performance degradation of the acquisition system. This paper proposes a novel two steps based bit sign transition cancellation method which can overcome the bit sign transition problem and remove or mitigate the CAF peak splitting impairments. The performance of the proposed technique has been comprehensively evaluated with Monte Carlo simulations in terms of detection and false alarm probabilities, which are presented by Receiver Operating Characteristic (ROC) and Signal-to-Noise-Ratio (SNR) curves. The test results show that the proposed acquisition technique can provide improved performance in comparison with the state-of-the-art acquisition approaches.

In this paper, the authors discuss a fully automatic berthing system and actual tests using a small training ship, Shioji Maru. The ship is about 440 gross tonnage and furnished with a controllable pitch propeller, a bow thruster and a stern thruster to which a computer can easily be linked. The system developed is composed of an electro-optical position measuring system and the computer software necessary for manoeuvring the ship.

The electro-optical position measuring system can measure a distance between the ship and a target on a berth within 4 cm accuracy and cover an area out to about 100 m range. The manoeuvring is divided into two stages. The first one is from a start line to a transition point off the final berth. At this point, the ship must be stopped in an alongside attitude to the berth. In the second stage, the ship is pushed by the thrusters in an athwartships direction towards the berth and the final speed at the berth must be limited to within 0.5 ms. The computer software generates an appropriate strategy following an approach line which has been determined in advance.

According to the actual tests under slightly rough sea conditions, the system could manoeuvre the ship along the approach line by a direct path and maintain her final speed within the predetermined limit.

Cooperative hunting with multiple Autonomous Underwater Vehicles (AUVs) not only needs the AUVs to cooperate, but also demands real-time path planning to catch up with evading targets. In this paper a time-based alliance mechanism to form efficient dynamic hunting alliances is proposed. After that, during the active hunting stage, an improved neural network model based on a Glasius Bio-inspired Neural Network (GBNN) is presented for path planning to immediately achieve tracking of an intelligent target. This study shows that the improved GBNN model has good performance in real-time hunting path planning. From the simulation studies as described in this paper, both the hunting alliance formation mechanism and the proposed real-time hunting path planning strategy show their advantages. The results show that the improved GBNN model proposed in this paper can work well in the control of multiple AUVs to hunt for intelligent evading targets in environments containing obstacles.

To solve the problem of identifying ship model parameters quickly and accurately with the least test data, this paper proposes a nonlinear innovation parameter identification algorithm for ship models. This is based on a nonlinear arc tangent function that can process innovations on the basis of an original stochastic gradient algorithm. A simulation was carried out on the ship Yu Peng using 26 sets of test data to compare the parameter identification capability of a least square algorithm, the original stochastic gradient algorithm and the improved stochastic gradient algorithm. The results indicate that the improved algorithm enhances the accuracy of the parameter identification by about 12% when compared with the least squares algorithm. The effectiveness of the algorithm was further verified by a simulation of the ship Yu Kun. The results confirm the algorithm's capacity to rapidly produce highly accurate parameter identification on the basis of relatively small datasets. The approach can be extended to other parameter identification systems where only a small amount of test data is available.

The fingerprint positioning (FP) algorithm has been investigated extensively owing to the fact that it can provide a relatively ideal indoor positioning result. However, the effectiveness of the fingerprint algorithm relies on the size of fingerprint database, which prevents the algorithm from being widely applied in practical applications. In this paper, an improved fingerprint algorithm with access point (AP) selection strategy and reference point (RP) selection strategy is proposed to reduce the size of the fingerprint database and improve the positioning accuracy. The experimental results show that the proposed algorithm can reduce the storage size of the fingerprint database by more than 42·64%. Moreover, compared with the FP algorithm, the fingerprint algorithm with segment characteristic distance (FP-SCD) and the fingerprint algorithm with RP selection strategy (FP-RPSS), the average positioning error of the proposed algorithm is reduced by 20·15%, 10·83% and 11·57%, respectively. Therefore, the proposed algorithm has a good application in real positioning scenarios.

This paper presents a framework for a strapdown Inertial Navigation System (INS) algorithm design by using Lie group and Lie algebra. The general way to solve Lie group differential equations is introduced. Investigations reveal that this general Lie group method provides a simpler unified way to solve differential equations involving direction cosine matrix, quaternion and dual quaternion, which are widely used in INS algorithm design. Furthermore, we also present a new INS algorithm based on the Special Euclidean group se(3) under the guidelines of Lie group method. Analyses show that se(3) algorithm has the same accuracy as a dual quaternion algorithm, this is also justified by numerical simulations. Though the se(3) algorithm has no improvements in accuracy, the general Lie group method used in the design process shows its brevity and uniformity.

Recent evidence has shown that the effect of a ship moving in shallow water and the resultant squat are not well understood. This paper reviews the general problem of a ship in shallow water and illustrates the corresponding resistance, trim and sinkage at both sub-critical and also at super-critical speeds.

The paper then reviews the various methods of predicting the squat of a ship in shallow water in the sub-critical range, which is applicable to most ships. It is suggested that the simple rule-of-thumb methods are, at best, unreliable and the paper gives examples of empirical methods which have been tested against various sets of data and seem to give more representative answers. A summary of the notation used is given at the end of the paper.

There are many scenarios where an integrated INS/GNSS navigation system may be required to operate in a high interference or weak signal environment. The GPS receiver may exploit the inertial aiding by operating with narrow tracking loop bandwidths in order to increase interference resistance. However, where a low grade INS is used, wider bandwidths are desirable to calibrate the INS errors effectively. This is important for GPS tracking loop aiding and sole-means inertial navigation during jamming. To obtain both effective INS calibration and jamming resistance, an adaptive tightly-coupled (ATC) INS/GPS integration architecture has been developed. The ATC technique has been assessed by simulation, showing that it provides a significant anti-jam margin over an INS/GPS with fixed tracking bandwidths selected for INS calibration. Compared to the deep (or ultra-tightly-coupled) integration techniques currently under development, ATC is a low cost anti-jam integration technique as it does not require a complete re-design of the navigation architecture. When there is too much interference for any GNSS signals to be tracked, the INS provides sole-means navigation. Thus, it is important to optimise the calibration of the INS when GNSS signals are available. To this end, the effects of estimating higher order inertial instrument errors and satellite range biases within the INS/GPS integration filter have been assessed.

A multi-region scene matching-based localisation system for automated navigation of Unmanned Aerial Vehicles (UAV) is proposed. This system may serve as a backup navigation error correction system to support autonomous navigation in the absence of a global positioning system such as a Global Navigation Satellite System. Conceptually, the system computes the location of the UAV by comparing the sensed images taken by an on board optical camera with a library of pre-recorded geo-referenced images. Several challenging issues in building such a system are addressed, including the colour variability problem and elimination of time-varying details from the pairs of images. The overall algorithm is an iterative process involving four sub-processes: firstly, exact histogram matching is applied to sensed images to overcome the colour variability issues; secondly, regions are automatically extracted from the sensed image where landmarks are detected via their colour histograms; thirdly, these regions are matched against the library, while eliminating inconsistent regions between underlying image pairs in the registration process; and finally the location of the UAV is computed using an optimisation procedure which minimises the localisation error using affine transformations. Experimental results demonstrate the proposed system in terms of accuracy, robustness and computational efficiency.

The positioning accuracy of the BeiDou Navigation Satellite System (BDS) can reach up to 10 m (95% confidence level) in both horizontal and vertical components. In order to improve the positioning performance for metre-level navigation, BDS pseudorange differential positioning has been proposed. We introduce the basic principles of BDS pseudorange differential positioning. Then based on the traditional Hatch filter, a modified Hatch filter for dual-frequency phase-smoothed pseudorange is introduced. The phase-smoothed pseudorange differential positioning, whose observations are smoothed by the modified Hatch filter using BDS B1 and B3 and Global Positioning System (GPS) L1 and L2 carrier-phase observations, are applied to determine the roving station's position. Three strategies are used for results analysis. The results show that the longer the baseline length is, the poorer positioning accuracy gets, and the positioning accuracy decline rate of the BDS B3 signal is higher than that of the BDS B1 signal, especially for long baselines. The percentages of the position deviations less than 3 m in horizontal component and 5 m in vertical component for BDS signals can reach up to 95 %.

In this contribution, an improved Extended Kalman Filter (EKF), named the Total Extended Kalman Filter (TEKF) is proposed for integrated navigation. It can consider the neglected random observed quantities which may appear in a dynamic model. In particular, this paper will consider the case of vision-based navigation. This algorithm is equipped with quadratic constraints and makes use of condition equations. The paper will show that the refined data from different sensors including a Global Positioning System (GPS) receiver, an Inertial Navigation System (INS) and remote sensors can be fused into a Constrained Total Extended Kalman Filter (CTEKF) algorithm. The CTEKF algorithm is applied to a case study in the Guilan province in the north of Iran. The results show the efficiency of the proposed algorithm.

This paper was presented at a meeting of the Institute in London on 18 February 1981 with Dr J. F. Kemp in the Chair. Captain Alderton discusses a variety of criteria for assessing economic optimal speeds and shows how sensitive these optima are to such constraints as port time, voyage distance and bunker costs.

The expression ‘optimum’ is frequently used very loosely and one often finds that the factor under consideration is only being optimized with reference to some, not all, of its dependent variables. A truly optimum speed for a ship can only be achieved by considering:

(i) What speeds the ship can actually achieve, taking into account various mechanical constraints, the state of the hull (fouling), the draft and the effect of the weather.

(ii) What speeds we would like the ship to achieve taking into account the costs, the profits and the pressure of schedules.

Analysis of helicopter accidents is fundamental to the development of effective mitigation measures. However, there are significant weaknesses in the current methods. This paper proposes a new structured framework for the analysis of accidents in helicopter operations, which includes the determination of the appropriate timeframe for analysis, establishment of terminological definitions, identification of the relevant accident variables and data sources, and the execution of a three-fold statistical analysis strategy. It is implemented in the context of worldwide offshore helicopter operations, enabling the identification of a number of areas for priority intervention including the need for a global harmonisation of accident data capture and dissemination, causal factor-based metrics for the calculation of accident rates, better pilot support for night-time and arrival operations, and a new safety paradigm to mitigate rare accidents. The framework is recommended for the analysis of helicopter accidents and incidents to support safety improvement.

Real-time and near real-time precise GPS positioning requires shorter GPS solution convergence time. Residual tropospheric delay, which exists as a result of the limitations of existing tropospheric correction models, is a limiting factor for quick GPS solution convergence. This paper proposes a new approach to tropospheric delay modelling, which overcomes the limitations of existing models. In this approach, the bulk of the tropospheric delay is accounted for using the NOAA-generated tropospheric correction model, while the residual tropospheric delay component is accounted for stochastically. First, the NOAA tropospheric correction model is used to generate daily time series of zenith total tropospheric delays (ZTDs) at ten IGS reference stations spanning North America for many days in 2006. The NOAA ZTDs are then compared with the new highly-accurate IGS tropospheric delay product to obtain daily residual time series at 5 minute intervals. Finally, the auto-covariance functions of the daily residual tropospheric delay series are estimated at each of the ten reference stations and then used to find the best empirical covariance function in the least squares sense. Of the three potential covariance functions examined, it is shown that the exponential cosine function gives the best fit most of the time, while the second-order Gauss-Markov model gives the worst fit. The first-order Gauss-Markov fits are close to those of the exponential cosine. Additionally, the model coefficients seem to be season independent, but change with geographical location.

In a waist-worn Pedestrian Navigation System (PNS) based on Dead-Reckoning (DR), heading drift caused by Micro-Electro-Mechanical System (MEMS) gyro bias is an essential factor affecting DR accuracy. Considering the characteristics of pedestrian navigation and the poor bias repeatability of MEMS gyros, this paper presents a standing calibration method for MEMS gyro bias. The current gyro biases for each boot can be calibrated accurately in the initial stage before walking. Since the attitude angles calculated by the output data from magnetic sensor and accelerometers do not drift, this paper applies the reverse algorithm of attitude updating to calculate the angular velocities of human motion. Then the gyro biases at each moment can be acquired by subtraction operation between the measured angular velocities from gyros and the calculated angular velocities of human motion. Finally, in order to restrain the random error caused by sensor noise, the calculated biases in the initial stage are smoothed, and consequently the optimal estimate of current gyro biases after each boot can be obtained. Still and dynamic turntable experiments and a walking experiment are performed to compare and analyse the proposed method and the Zero Angular Rate Update (ZARU) method. Experimental results show that the proposed method can also calibrate the gyro bias accurately in the case of body swaying.

A dual-axis rotational Inertial Navigation System (INS) has received wide attention in recent years because of high performance and low cost. However, some errors of inertial sensors such as stochastic errors are not averaged out automatically during navigation. Therefore a Twice Position-fix Reset (TPR) method is provided to enhance accuracy of a dual-axis rotational INS by compensating stochastic errors. According to characteristics of an azimuth error introduced by stochastic errors of an inertial sensor in the dual-axis rotational INS, both an azimuth error and a radial-position error are much better corrected by the TPR method based on an optimised error propagation equation. As a result, accuracy of the dual-axis rotational INS is prominently enhanced by the TPR method, as is verified by simulations and field tests.

The Autonomous Navigation System (ANS) constitutes a critical key enabling technology required for operating Maritime Autonomous Surface Ships (MASS). To assure the safety of MASS operations, the effective identification of potential objects and target ships interacting with the own MASS is quintessential. This study proposes a systematic method to identify the items interacting with the own MASS. This method is based on a similar approach previously employed for the encountering items’ identification in robotics, which is customised herein for the MASS needs. The developed method is applied to a short-sea shipping MASS. The environmental features, agents and objects related to her navigation are identified and ranked based on the frequency of encounter and the potential collision consequences. The results demonstrate the ability of the method to identify additional items in comparison to Automatic Identification System based data. The interactions with the small ships are considered as the most critical, due to their potential accidental consequences and their exhibited high frequency of encounter. This study results are employed to support the ANS design and testing of the investigated ship.

Based on the candidate architectures of the libration point satellite navigation system proposed in our previous work, a navigation performance study is conducted in this paper to verify the cislunar navigation ability of the proposed system. Using scalar satellite-to-satellite range measurement between the user and libration point navigation satellites, a virtual lunar exploration mission scenario is developed to verify the navigation performance of the candidate Earth-Moon L1,2,4,5 four-satellite constellations. The simulation results indicate that the libration point satellite navigation system is available for cislunar navigation and the navigation accuracy of a few tens of metres can be achieved for both the trans-lunar cruise and lunar orbit phase. Besides that, it is also found that the navigation accuracy of the libration point satellite navigation system is sensitive to the orbit of the L1 satellite. Once the L1 navigation satellite is located in the Halo orbit or vertical Lyapunov orbit, the proposed system can present a better navigation performance in cislunar space.