This paper is intended to provide an outline of how the lead and line formed a vital, but often overlooked, role in safe navigation during the 16th Century, with some comments on its later use up to, and into the 20th Century. During this period, the development of the more mathematical dead-reckoning and the more exciting astro-navigation attracted the attention of the literate commentators who were responsible for record keeping while the often illiterate sailors got on with practising their craft. Also, May (1970), has commented that, “the navigators during the great age of discovery must have made extensive use of the lead and line, but references are extremely sparse, for all their rough log-books were destroyed and only the most important references to their navigational proceedings were copied into the fair accounts of their voyages which have come down to us.”

Code Differential Global Positioning System (DGPS) is widely used in satellite navigation and positioning because of its simple algorithm and preferable precision. Multi-Global Navigation Satellite System (GNSS) is expected to enhance the accuracy, reliability and availability of Differential GNSS (DGNSS) positioning. Traditional DGNSS models should set separate clock parameters due to the clock differences between the different systems. Awareness of the Inter-System Bias (ISB) could help to maximise the redundancy of the positioning model, thus improving the performance of multi-GNSS positioning. This paper aims to examine the inter-system bias of GPS/GLONASS/BeiDou (BDS)/Galileo and their benefits in DGNSS positioning. Results show that Differential ISB (DISB) characteristics vary with different receiver types and systems. The size of DISB could reach metre-level and the precision of estimated DISBs can reach approximately several centimetres within tens of epochs. Therefore, a new real-time DGNSS model that accounts for ISB is proposed. After differential ISBs are initialised, positioning with four satellites from arbitrarily the same or different systems can be realised. Moreover, compared with the traditional DGNSS model, the precision of the positioning results with the new model are obviously improved, especially in harsh environments.

Ship collision avoidance involves helping ships find routes that will best enable them to avoid a collision. When more than two ships encounter each other, the procedure becomes more complex since a slight change in course by one ship might affect the future decisions of the other ships. Two distributed algorithms have been developed in response to this problem: Distributed Local Search Algorithm (DLSA) and Distributed Tabu Search Algorithm (DTSA). Their common drawback is that it takes a relatively large number of messages for the ships to coordinate their actions. This could be fatal, especially in cases of emergency, where quick decisions should be made. In this paper, we introduce Distributed Stochastic Search Algorithm (DSSA), which allows each ship to change her intention in a stochastic manner immediately after receiving all of the intentions from the target ships. We also suggest a new cost function that considers both safety and efficiency in these distributed algorithms. We empirically show that DSSA requires many fewer messages for the benchmarks with four and 12 ships, and works properly for real data from the Automatic Identification System (AIS) in the Strait of Dover.

The precise autonomous navigation for deep space exploration by combination of multi-source observation data is a key issue for probe control and scientific applications. In this paper, the performance of an integrated Optical Celestial Navigation (OCN) and X-ray Pulsars Autonomous Navigation (XNAV) system is investigated for the orbit of Mars Pathfinder. Firstly, OCN and XNAV single systems are realised by an Unscented Kalman Filter (UKF). Secondly, the integrated system is simulated with a Federated Kalman Filter (FKF), which can do the information fusion of the two subsystems of UKF and inherits the advantages of each subsystem. Thirdly, the performance of our system is evaluated by analysing the relationship between observation errors and navigation accuracy. The results of the simulation experiments show that the biases between the nominal and our calculated orbit are within 5 km in all three axes under complex error conditions. This accuracy is also better than current ground-based techniques.

Spatial indexing technology is widely used in Geographic Information Systems (GIS) and spatial databases. As a data retrieval technology, spatial indexing is becoming increasingly important in the big-data age. The purpose of this study is to propose a unified indexing strategy for the mixed data of a future marine GIS. First, data organisation of the system is described. Second, the display condition of each type of data is introduced. These conditions are the basis for the construction of a unified indexing structure. Third, a unified indexing structure for mixed data is presented. The construction process and the search method of the indexing structure are described. Finally, we implement the indexing strategy in our system “Automotive Intelligent Chart Three-dimensional Electronic Chart Display and Information Systems” (AIC 3D ECDIS). Our strategy can provide fast and integrated data retrieval. The spatial indexing strategy we propose breaks through the limitation of data types in our system. It can also be applied in other GIS systems. With the advent of the big-data age, mixed data indexing will become more and more important.

In this paper, we consider the joint estimation of the position of a spacecraft and debris in Earth orbit to achieve spacecraft localisation based on angular measurements and precise measurements of the debris relative to the spacecraft. The dynamic model of the spacecraft caters for several perturbing effects, such as Earth and Moon gravitational field asymmetry and the Earth's oblateness effect. The Moon's position is assumed to be accurately known for the purposes of simulation from published Jet Propulsion Laboratory (JPL) ephemerides. The measurement process is based on the elevation and azimuth of the Moon and the Sun with respect to the spacecraft reference system. Range measurements are not assumed to be available. Position and velocity of the spacecraft are estimated by using the Unscented Kalman Filter (UKF). The performance of the filters are evaluated on an example of an Earth-orbiting satellite at an altitude over 1200 km with measurements of the directions of the Moon and the Sun only. It is shown that the estimates of position and velocity components track the corresponding simulated position and velocity components.

The Automatic Identification System (AIS) receiver on board the main satellite of the TianTuo-3 constellation, LvLiang-1, is a new generation of AIS receiver. Having partly solved the signal conflict problems and with larger coverage over the ground, the AIS receiver on board TianTuo-3 greatly improves the signal detection ability. The data received by the AIS receiver during the TianTuo-3 debugging stage is employed for detailed analysis in this paper. Results include: TianTuo-3 implements four-frequency detection at the same time, and a time-flag is inserted into the received AIS data, a small portion of Class A vessels (at least 1480) have been equipped with AIS sending the long range AIS broadcast message with two new frequency channels and the hourly averaged count of the message received by TianTuo-3’s AIS is between 1500 ~ 2500. This AIS receiver is capable of real-time tracking a single vessel. In conclusion, the TianTuo-3 space-based AIS receiver is capable of continuously receiving AIS messages sent by global maritime vessels.

This paper is aimed at the risk assessment of operational safety for oil tankers. Based on the operational features of oil tankers and relevant literature, the Risk Factors (RFs) of operational safety were first identified. A revised risk matrix based on a fuzzy Analytical Hierarchy Process (AHP) approach was then proposed to assess the risk classes of the RFs. Finally, to validate the research model, the oil tanker fleet of Chinese Petroleum Corporation (CPC) in Taiwan was empirically investigated. The results can provide practical information for oil carriers to improve their ships' operational safety. Furthermore, the revised risk matrix may provide a theoretical reference for methodological researches in safety risk assessments.

This paper is concerned with the preliminary localisation, orbit determination and model-based path forecasting of space debris based on a robust procedure. In this work, an in-orbit observer utilises only relative bearing observations iteratively. To this end, the problem is first formulated in order to calculate the distance vector between the space debris and any orbiting observer. Afterwards, the obtained position vector is corrected through an Extended Kalman Filter (EKF) for shrinking the sensor and process errors and increasing robustness of the computations in the presence of uncertainties. After preliminary positioning, the related classical orbital elements are acquired via the predicted position and velocity vectors using a hybrid technique. Extensive simulations demonstrate the efficacy and robustness of the aforementioned method, and in particular it is verified that the proposed scheme is capable of producing a suitable solution for preliminary localisation and orbit determination of space debris based on the presented space-based observation, which is practical in phasing and chasing manoeuvres of any grabber space robot.

Nonlinear least squares estimations have been widely applied in positioning. However, nonlinear least squares estimations are generally biased. As the Gauss-Newton method has been widely applied to obtain a nonlinear least squares solution, we propose an iterative procedure for obtaining unbiased estimations with this method. The characteristics of the linearization error are discussed and a systematic error source of the linearization error needs to be removed to guarantee the unbiasedness. Both the geometrical condition and the statistical condition for unbiased nonlinear least squares estimations are revealed. It is shown that for long-distance observations of high precision, or for a positioning configuration with the lowest Geometric Dilution Of Precision (GDOP), the nonlinear least squares estimations tend to be unbiased; but for short-distance cases, the bias in the nonlinear least squares solution should be estimated to obtain unbiased values by removing the bias from the nonlinear least squares solution. The proposed results are verified by the Monte Carlo method and this shows that the bias in nonlinear least squares solution of short-distance distances cannot be ignored.

An X-ray pulsar/starlight Doppler deeply-integrated navigation method is proposed in this paper. A starlight Doppler measurement-aided phase propagation model, which can remove the orbital effect within the recorded photon Time Of Arrivals (TOAs), is derived, and guarantees that the pulse phase can be extracted from the converted photon TOAs using computationally efficient methods. Some simulations are performed by a hardware-in-loop system to verify the performance of the integrated pulse phase estimation method as well as of the integrated navigation method. The integrated pulse phase estimation method could achieve an estimation performance similar to the existing method for orbiting vehicles at the cost of much less computational complexity, is capable of handling the signals of millisecond pulsars, and is applicable to various vehicles. In addition, the proposed integrated navigation method could provide reliable positioning results for various vehicles.

The maritime domain is the most utilised environment for bulk transportation, making maritime safety and security an important concern. A major aspect of maritime safety and security is maritime situational awareness. To achieve effective maritime situational awareness, recently many efforts have been made in automatic anomalous maritime vessel movement behaviour detection based on movement data provided by the Automatic Identification System (AIS). In this paper we present a review of state-of-the-art automatic anomalous maritime vessel behaviour detection techniques based on AIS movement data. First, we categorise some approaches proposed in the period 2011 to 2016 to automatically detect anomalous maritime vessel behaviour into distinct categories including statistical, machine learning and data mining, and provide an overview of them. Then we discuss some issues related to the proposed approaches and identify the trend in automatic detection of anomalous maritime vessel behaviour.

The purpose of this study is to determine the navigation efficiency for transiting from various ports in Asia and Rotterdam in Europe via the Northern Sea Route. Navigation efficiency was derived from fuel consumption ratios. Preliminary research results showed that fuel consumption and the amount of carbon dioxide emissions was reduced by transiting from various ports through the European Sea Route, and the navigation efficiencies of the various ports ranked in the following descending order: Yokohama - Busan - Shanghai - Kaohsiung - Hong Kong - Singapore. The higher the ratio was, the lower the navigation efficiency of using the Northern Sea Route, i.e. more fuel was consumed and travel costs were higher. In contrast, the lower the ratio was, the higher the navigation efficiency, i.e. less fuel was consumed and travel costs were lower. Recommendations were discussed in the study.

Serious accidents in the marine and offshore industry have underscored the need for safety evaluation of maritime operations using risk and safety analysis methods which have become a powerful tool in identifying technical solutions and operational management procedures. Given that Fault Tree Analysis (FTA) is a known methodology used for analysing engineering systems, the approach is usually conducted using known failure data. But most offshore operations are conducted in a challenging and uncertain environment and the failure data of some of these systems are usually unavailable requiring a flexible and yet robust algorithm for their analysis. This paper therefore seeks to analyse the complex structure of Offshore Supply Vessel (OSV) collision with platforms by incorporating a Fuzzy Fault Tree Analysis (FFTA) method. Fuzzy set theory provides the flexibility to represent vague information from the analysis process. The methodology is structured in such a manner that diverse sets of data are integrated and synthesized for analysing the system. It is envisaged that the proposed method could provide the analyst with a framework to evaluate the risks of collision enabling informed decisions regarding the deployments of resources for system improvement.

In the effort to quantify Automatic Dependent Surveillance Broadcast (ADS-B) system safety, the authors have identified potential ADS-B failure modes in Syd Ali et al. (2014). Based on the findings, six potential hazards of ADS-B are identified in this paper. The authors then applied the Probabilistic Safety Assessment approach which includes Fault Tree Analysis (FTA) and Importance Analysis methods to quantify the system safety. FTA is applied to measure ADS-B system availability for each identified hazard while Importance Analysis is conducted to identify the most significant failure modes that may lead to the occurrence of the hazards. In addition, risk significance and safety significance of each failure mode are also identified. The result shows that the availability for the ADS-B system as a sole surveillance means is low at 0·898 in comparison to the availability of ADS-B system as supplemental or as primary means of surveillance at 0·95 and 0·999 respectively. The latter availability values are obtained from Minimum Aviation System Performance Standards (MASPS) for Automatic Dependent Surveillance-Broadcast (DO-242A).

This paper offers an algorithm for enhancement of positioning accuracy of a quad-rotor flying robot, based on jerk and jounce of motion. The suggested method utilises the first and second numerical derivatives of the vehicle's acceleration and augments the mathematical model in the estimation process. For this purpose, the Kalman Filter (KF) is implemented for integration of a Strapdown Inertial Navigation System (SINS) and Global Navigation Satellite System (GNSS). The required data are collected from a low-cost/quality Micro Electromechanical Sensors (MEMS) during an assisted flight. For increasing the precision and accuracy of the collected data, all instruments including accelerometers, gyroscopes and magnetometers are calibrated before the experiments. Moreover, to reduce and limit the measurement noises of the MEMS sensor, a low-pass filter is applied; this is while sensors in the autopilot are affected by high levels of noise and drift, which makes them inappropriate for accurate positioning. The experimental results exhibit an improvement in positioning and altitude sensing through augmentation of the loosely coupled SINS/GNSS navigation method.