Global Navigation Satellite System (GNSS) shadow matching is a new positioning technique that determines position by comparing the measured signal availability and strength with predictions made using a three-dimensional (3D) city model. It complements conventional GNSS positioning and can significantly improve cross-street positioning accuracy in dense urban environments. This paper describes how shadow matching has been adapted to work on an Android smartphone and presents the first comprehensive performance assessment of smartphone GNSS shadow matching. Using GPS and GLONASS data recorded at 20 locations within central London, it is shown that shadow matching significantly outperforms conventional GNSS positioning in the cross-street direction. The success rate for obtaining a cross-street position accuracy within 5 m, enabling the correct side of a street to be determined, was 54·50% using shadow matching, compared to 24·77% for the conventional GNSS position. The likely performance of four-constellation shadow matching is predicted, the feasibility of a large-scale implementation of shadow matching is assessed, and some methods for improving performance are proposed. A further contribution is a signal-to-noise ratio analysis of the direct line-of-sight and non-line-of-sight signals received on a smartphone in a dense urban environment.

Exact motion estimation is a major task in autonomous navigation. The integration of Inertial Navigation Systems (INS) and the Global Positioning System (GPS) can provide accurate location estimation, but cannot be used in a GPS denied environment. In this paper, we present a tight approach to integrate a stereo camera and low-cost inertial sensor. This approach takes advantage of the inertial sensor's fast response and visual sensor's slow drift. In contrast to previous approaches, features both near and far from the camera are simultaneously taken into consideration in the visual-inertial approach. The near features are parameterised in three dimensional (3D) Cartesian points which provide range and heading information, whereas the far features are initialised in Inverse Depth (ID) points which provide bearing information. In addition, the inertial sensor biases and a stationary alignment are taken into account. The algorithm employs an Iterative Extended Kalman Filter (IEKF) to estimate the motion of the system, the biases of the inertial sensors and the tracked features over time. An outdoor experiment is presented to validate the proposed algorithm and its accuracy.

Understanding the impact of technology introduction on users’ attitudes toward and behaviour with technology is increasingly important. This paper suggests several research questions that are important as Wearable, Immersive Augmented Reality (WIAR) systems are introduced in ship navigation: what contributions to navigation decision-making might be made by WIAR technology? And how do these influences relate to safety in marine transportation? This paper begins with an overview of information needs for shipboard navigation and piloting, and then describes the evolution of shipboard decision support systems for navigation, including the emergence of wearable, immersive augmented reality systems. An assessment of piloting and navigation information needs and the capabilities of WIAR are then presented, which suggests a conceptual model for studying the impact of WIAR systems on performance and safety in marine transportation. Conclusions and future work to explore the role and contribution of WIAR technology to the safety of navigation are then presented.

A new Bayesian approach for multiple satellite faults detection and exclusion is proposed by introducing a classification variable to each satellite observation. If we treat this classification variable as random and assume a prior distribution for it, then a rule for satellite fault detection and exclusion based on the posterior probabilities of the classification variables is constructed under the framework of Bayesian hypothesis testing. Secondly, the Gibbs sampler is introduced to compute the posterior probabilities of the classification variables. Then the implementation for a Bayesian Receiver Autonomous Integrity Monitoring (RAIM) algorithm is designed with the Gibbs sampler. Finally, different schemes are designed to evaluate the performance of the new Bayesian RAIM algorithm in the case of multiple faults. We compare the method in this paper with the Range Consensus (RANCO) method. Experiments illustrate that the proposed algorithm in this paper is capable of detecting and eliminating multiple satellite faults, and the probability of correctly detecting faults is high.

Precise Point Positioning (PPP) performance is improving under the ongoing Global Positioning System (GPS) modernisation program. The availability of the third frequency, L5, enables triple-frequency combinations. However, to utilise the modernised L5 signal along with the existing GPS signals, P1-C5 differential code bias must be determined. In this paper, the global network of Multi-Global Navigation Satellite System Experiment (MGEX) stations was used to estimate P1-C5 satellites differential code biases $(DCB_{P1 - C5}^S )$. Mathematical background for triple-frequency linear combinations was provided along with the resultant noise and ionosphere amplification factors. Nine triple-frequency linear combinations were chosen, based on different criteria, for processing the modernised L5 signal along with the legacy GPS signals. Finally, test results using real GPS data from ten MGEX stations were provided showing the benefits of the availability of the third frequency on PPP solution convergence time and the precision of the estimated parameters. It was shown that triple-frequency combinations could improve the PPP convergence time and the precision of the estimated parameters by about 10%. These results are considered promising for using the modernised GPS signals for precise positioning applications especially when the fully modernised GPS constellation is available.

Cooperative Localisation (CL) technology is required in some situations for Multiple Unmanned Underwater Vehicle (MUUVs) missions. During the CL process, the Relative Localisation Information (RLI) of the master UUV is transmitted to slave UUVs via acoustic communication. In the underwater environment, the RLI is subject to a random time delay. Considering the time delay characteristic of the RLI during the acoustic communication, a Moving Horizon Estimation (MHE) method with a Delayed Extended Kalman Filter (DEKF)-based arrival cost update law is presented in this paper to obtain an accurate and reliable estimation of present location. Additionally, an effective computation method for the MHE method is employed, in which the “Lower Upper” (LU) factorization is used to compute the solution of the Karush-Kuhn-Tucker (KKT) system. At the end of this paper, simulation results are presented to prove the superiority and practicality of the proposed MHE algorithm.

Aiming at improving the poor real-time performance of existing nonlinear filtering algorithms applied to spacecraft autonomous navigation based on Global Positioning System (GPS) measurements and simplifying the algorithm design of navigation algorithms, a spacecraft autonomous navigation algorithm based on polytopic linear differential inclusion is proposed in this paper. Firstly, it is demonstrated that the nonlinear estimation error system of spacecraft autonomous navigation can be modelled as a polytopic linear differential inclusion system model according to the idea of global linearization. Thus, the filtering of a nonlinear system simplified to a filtering of a polytopic linear system with coefficients. Secondly, Tensor-Product (TP) model transformation is applied to determine the polytopic linear differential inclusion system model. The model error introduced by global linearization is reduced and the compromise between computational complexity and modelling accuracy is realised. Finally, a spacecraft autonomous navigation algorithm based on polytopic linear differential inclusion is designed by combining multi-model Kalman filtering with data fusion. Compared with an Extended Kalman Filter (EKF), the proposed algorithm is simpler and easier to implement since it need not update the Jacobian matrices online. Simulation results demonstrate the same estimation accuracy of the proposed algorithm to that of EKF.

A novel relative spacecraft attitude and position estimation approach based on an Unscented Kalman Filter (UKF) is derived. The integrated sensor suite comprises the gyro sensors on each spacecraft and a vision-based navigation system on the slave spacecraft. In the traditional algorithm, an assumption that the master's body frame coincides with its Local Vertical Local Horizontal (LVLH) frame is made to construct the line-of-sight observations for convenience. To solve this problem, two relative quaternions that map the master's LVLH frame to the slave and master body frames are involved. The general relative equations of motion for eccentric orbits are used to describe the positional dynamics. The implementation equations for the UKF are derived. A modified version of the UKF is presented based on the averaging-quaternion algorithm. Simulation results indicate that the proposed filters provide more accurate estimates of relative attitude and position than the Extended Kalman Filter (EKF).

A new nonlinear robust filter is proposed in this paper to deal with the outliers of an integrated Global Positioning System/Strapdown Inertial Navigation System (GPS/SINS) navigation system. The influence of different design parameters for an H∞ cubature Kalman filter is analysed. It is found that when the design parameter is small, the robustness of the filter is stronger. However, the design parameter is easily out of step in the Riccati equation and the filter easily diverges. In this respect, a singular value decomposition algorithm is employed to replace the Cholesky decomposition in the robust cubature Kalman filter. With large conditions for the design parameter, the new filter is more robust. The test results demonstrate that the proposed filter algorithm is more reliable and effective in dealing with the outliers in the data sets produced by the integrated GPS/SINS system.

The predictions of Length-Of-Day (LOD) are studied by means of Gaussian Process Regression (GPR). The EOP C04 time-series with daily values from the International Earth Rotation and Reference Systems Service (IERS) serve as the data basis. Firstly, well known effects that can be described by functional models, for example effects of the solid Earth and ocean tides or seasonal atmospheric variations, are removed a priori from the C04 time-series. Only the differences between the modelled and actual LOD, i.e. the irregular and quasi-periodic variations, are employed for training and prediction. Different input patterns are discussed and compared so as to optimise the GPR model. The optimal patterns have been found in terms of the prediction accuracy and efficiency, which conduct the multi-step ahead predictions utilising the formerly predicted values as inputs. Finally, the results of the predictions are analysed and compared with those obtained by other prediction methods. It is shown that the accuracy of the predictions are comparable with that of other prediction methods. The developed method is easy to use.

The purpose of this paper is to discuss the safety of ship berthing operations in port. Based on the features of ship's berthing operations and relevant literature, the Safety Factors (SFs) of ship berthing at docks are first investigated. A Safety Index (SI) with a Fuzzy Analytic Hierarchy Process (AHP) model is then proposed to assess those SFs from port marine pilots, by which port managers and ship carriers may make policies to improve ship berthing safety. To validate the model, berthing operations at Kaohsiung Port in Taiwan were empirically investigated. The results indicate the main safety factors affecting ship berthing at port docks are: working concentration, the condition of mooring lines, emergency response, port policy of improving business and berth length. Based on those results, the theoretical and managerial implications for ship berthing safety at dock are finally discussed.

Recently, a basic pattern of coast seaway system networking has been established in China. As a result, a large number of precautionary areas will be gradually established. Because of the high frequency of ships' encounters and accidents, these precautionary areas have been a weak but important facet of ships' routeing. Navigational Traffic Conflict Technique (NTCT) was introduced to quantitatively evaluate the safety of precautionary areas. Focusing on traffic conflict, the calculation method of navigational traffic conflict points is discussed, and a comparison analysis of the two editions (2002 and 2008) of Yangtze estuary ships’ routeing is performed. Then the automatic acquisition system of navigational traffic conflict data that can be used in the quantitative analysis of the influence degree of a single traffic flow on the whole precautionary area safety is developed, and the left-turning traffic flows of Yangtze estuary ships’ routeing precautionary areas B are taken as an example. This article establishes a foundation for the precautionary area safety analysis system, and provides the decision basis for policy making in optimisation of geometric design and traffic organisation of precautionary areas.

This study aims to evaluate ship collision frequency in port fairways. One case study is created using one month's real-time ship movement data from five major Singapore port fairways. Results show that tankers account for the biggest proportion in the Temasek fairway, whereas the percentage of Roll-on-Roll-Off (RORO) and passenger ships is quite small in the Temasek fairway, Sinki fairway, Jong fairway and Southern fairway. Tankers and container ships are the two major ship types involved in dangerous encounters. The largest number of dangerous head-on and overtaking encounters is located in the Jong fairway. The majority of dangerous crossing encounters have occurred in the West Keppel fairway and Jong fairway. Ship collision frequency at night is found to be significantly higher than during the day in these fairways.

Would an increased emphasis on cost-effectiveness and markedly reduced controller workload/costs determine the Four-Dimensional Air Traffic Management (4D ATM) Concept – a mindset change? Are there workable concepts that focus on flightpath conformance monitoring rather than a combination of conformance and hazard monitoring? Fundamental criteria for a conformance management-based system are identified to meet workload and cost goals. A ‘Global Navigation Satellite System (GNSS)/Feedback Concept’ is sketched, with radical ingredients to convert GNSS's accurate position fixes into accurate aircraft flightpath navigation. This eliminates air/ground trajectory synchronisation processing, and focuses conflict probing/planning tools on non-conforming flights. This concept would need to address key Human Factor concerns satisfactorily.