Although AIS is already in use in a range of vessels, there has been little public discussion on how AIS should interact with the COLREGS in practice. The objective of this paper is to make a contribution to that debate, while recognising that “best practice” will evolve as more practical experience is obtained. The paper suggests the approach that should be adopted in several areas, but concludes that, overall, AIS is nothing more than one of several tools that should enable mariners to fulfil their existing obligations under the COLREGS.

This paper formed the basis of a highly successful talk at the RIN's AIS 03 in Church House London on 24th/25th November 2003. The authors are Tees Bay Pilots and have used their expertise and knowledge to survey and examine the introduction and progress of AIS.

Licensed mariners carried out two simulated navigation studies testing electronic chart and information display systems (ECDIS) against paper chart navigation. In the first study, six mariners each completed approaches to Halifax, Nova Scotia, harbour with good and bad visibility and a range of wind and currents. Conditions included chart with radar, ECDIS with radar overlay and ECDIS with separate radar. ECDIS produced better performance and a smaller workload than paper charts and the radar overlay was slightly better than the separate radar display. In the second study, six new mariners completed exercises with low visibility and heavy or light radar traffic using ECDIS with radar overlay, ECDIS without overlay and ECDIS with optional overlay. Mariners preferred the optional overlay but all three conditions produced about equal performance. Based on mariners' performance and expressed preference, we recommend that ECDIS systems provide optional radar overlays.

Predicting the tide in four ports, the Admiralty Tide Table (ATT) came out in early 1833. The table was for London and three naval dockyards. The observations at those dockyards, from which the ATT was first made, have recently come to light (Anonymous, 1833). This paper exposes the circumstance of the tables' construction; it is also an analysis of the later part of the observation series. The analysis is a comparison of the difference between observation and contemporary prediction, and to tides synthesised from the modern method. The ATT were only admitted into production after comparisons were made to its competitors. Those comparisons were for London alone and a recent study also concentrates on that one area. This study extends comparison to the remaining three-quarters of the early ATT: to Sheerness, Portsmouth and Plymouth.

This Anderson Memorial Lecture was given to the Boscombe Down branch of the Institute on 19 February 2004. In the lecture Pinky Grocott, a distinguished navigator and past President of the Institute, recounts the history of the formation of Ferry Command set up to ensure the safe and efficient delivery of aircraft from North America to the UK during World War II. He then provides personal insights into his role as a young first-tour RAF navigator employed in the Command and describes the contemporary navigation practice.

Current Eurocontrol Safety Regulation Commission (SRC) policy says that the Air Traffic Management (ATM) system (including safety minima) must be demonstrated through risk assessments to meet the Target Level of Safety (TLS) without needing to take safety nets (such as Short Term Conflict Alert) into account. This policy is wrong. The policy is invalid because it does not build rationally and consistently from ATM's firm foundations of TLS and hazard analysis. The policy is bad because it would tend to retard safety improvements. Safety net policy must rest on a clear and rational treatment of integrated ATM system safety defences. A new safety net policy, appropriate to safe ATM system improvements, is needed, which recognizes that safety nets are an integrated part of ATM system defences. The effects of safety nets in reducing deaths from mid-air collisions should be fully included in hazard analysis and safety audits in the context of the TLS for total system design.

With the European Commission (EC) and European Space Agency's (ESA) plans to develop a new satellite navigation system, Galileo and the modernisation of GPS well underway the integrity of such systems is as much, if not more, of a concern as ever. Receiver Autonomous Integrity Monitoring (RAIM) refers to the integrity monitoring of the GPS/Galileo navigation signals autonomously performed by the receiver independent of any external reference systems, apart from the navigation signals themselves. Quality measures need to be used to evaluate the RAIM performance at different locations and under various navigation modes, such as GPS only and GPS/Galileo integration, etc. The quality measures should include both the reliability and localizability measures. Reliability is used to assess the capability of GPS/Galileo receivers to detect the outliers while localizability is used to determine the capability of GPS/Galileo receivers to correctly identify the detected outlier from the measurements processed.

Within this paper, the fundamental equations required for effective outlier detection and identification algorithms are described together with the measures of reliability and localizability. Detailed simulations and analyses have been performed to assess the performances of GPS only and integrated GPS/Galileo navigation solutions with respect to reliability and localizability. Simulation results show that, in comparison with the GPS-only solution, the localizability of the integrated GPS/Galileo solution can be improved by up to 270%. The results also indicate an expectation of a considerable increase in the sensitivity to outliers and accuracy of their estimation with the augmentation of the Galileo system with the existing GPS system.

Attitude estimation systems often use two or more different sensors to increase reliability and accuracy. Although gyroscopes do not have problems like limited range, interference, and line of sight obscuration, they suffer from slow drift. On the other hand, inclinometers are drift-free but they are sensitive to transverse accelerations and have slow dynamics. This paper presents an extended Kalman filter (EKF)-based data fusion algorithm which utilizes the complementary noise profiles of these two types of sensors to extend their limits. To avoid complexities of dynamic modelling of the platform and its interaction with the environment, gyro modelling will be used to implement indirect (error state) form of the Kalman filter. The great advantage of this approach is its independence from the structure of the platform and its applicability to any system with a similar set of sensors. Separate bias formulation of the Kalman filter will be used to reduce the computational complexity of the algorithm. In addition, a systematic approach based on wavelet decomposition will be utilized to estimate noise covariances used in the Kalman filter formulation. This approach solves many of the convergence problems encountered in the implementation of EKF due to the choice of covariance matrices. Experimental implementation of the estimator shows the excellent performance of the filter.

In this paper, the Auto-Regressive Moving-Averaging (ARMA) neural networks (NNs) will be incorporated for predicting the differential Global Positioning System (DGPS) pseudorange correction (PRC) information. The neural network is employed to realize the time-varying ARMA implementation. Online training for real-time prediction of the PRC enhances the continuity of service on the differential correction signals and therefore improves the positioning accuracy. When the PRC signal is lost, the ARMA neural network predicted PRC would temporarily provide correction data with very good accuracy. Simulation is conducted for evaluating the ARMA NN based DGPS PRC prediction accuracy. A comparative performance study based on two types of ARMA neural networks, i.e. Back-propagation Neural Network (BPNN) and General Regression Neural Network (GRNN), will be provided.

An adaptive integrated Kalman filtering based on the adjustment outputs of local navigation sensors and the outputs of a dynamic or kinematic state model is presented, which avoids the correlations of the local Kalman filtering outputs affected by the same disturbances of the dynamic state model. It has the advantage of rigor in theory and simple in calculation as well as adaptive in the various local navigation outputs. An integrated navigation estimator that is similar to the federated Kalman filtering is given as an initial estimate of a state based on the information sharing principle, but without any dynamic model information. An adaptive integrated fusion of the local navigation outputs and the dynamic model information is followed, in which the weights of the local navigation outputs and the dynamic model outputs are determined based on their differences from the integrated navigation results. The processing algorithms, logic, and associated computer burden are similar to those of federated filter. A simulated example is given to show the effectiveness of the new adaptive integrated navigation algorithm.

We propose in this paper a method to enhance the performance of a coupled global positioning/inertial navigation system (GPS/INS) for land navigation applications during GPS signal loss. Our method is based on the use of an artificial neural network (ANN) to intelligently aid the GPS/INS coupled navigation system in the absence of GPS signals. The proposed enhanced GPS/INS is tested in the dynamic environment of a land vehicle navigating around a closed path on the METU campus and we provide the results. Our GPS/INS+ANN system performance is thus demonstrated with a land trial.