This paper presents an investigation of the precise point positioning (PPP) performance of a combined solution from BDS-2 and BDS-3 satellites. To simultaneously process different BDS signal observations, i.e., B1/B1C, B2/B2a and B3C, undifferenced and uncombined observations with ionosphere delay constrained by the deterministic plus stochastic ionosphere model are used in the basic model. Special attention is paid to code bias and receiver clock parameters in the derivation of the observation model. The analysis is carried out using more than one-month data for BDS-2 and BDS-3 collected at the CANB, DWIN, KNDY and PETH stations in the Asia-Pacific region. The results suggest that compared with BDS-2 alone, the BDS-2 and BDS-3 solution provides significantly more accurate PPP, with increases of 28%, 21% and 5% in the up, north and east directions, respectively. In addition, the average root mean square error decreases to 0·21, 0·13 and 0·16 m for the three directions. Furthermore, the PPP convergence time for BDS-2 and BDS-3 is about 1·5 h and less than 1 h for the horizontal and vertical components, respectively, whereas that for BDS-2 alone is about 2·3 h for both directions.

Real-time and accurate fault detection and isolation is very important to ensure the reliability and precision of integrated inertial navigation and global navigation satellite systems. In this paper, the detection performance of a residual chi-square method is analysed, and on this basis an improved method of fault detection is proposed. The local test based on a standardised residual is introduced to detect and identify faulty measurements directly. Differing from the traditional method, two appropriate thresholds are selected to calculate the weight factor of each measurement, and the gain matrix is adjusted adaptively to reduce the influence of the undetected faulty measurement. The sliding window test, which uses past measurements, is also added to further improve the fault detection performance for small faults when the local test based on current measurements cannot judge whether a fault has occurred or not. Several simulations are conducted to evaluate the proposed method. The results show that the improved method has better fault detection performance than the traditional detection method, especially for small faults, and can improve the reliability and precision of the navigation system effectively.

Past research showed that traditional assessment methods that required seafarer students to construct responses based on memorisation and analysing information presented in absence of real-world contexts (e.g. oral examinations and multiple-choice questions) disengaged the students from learning. Memorising information is a lower-order cognitive ability, failure in which led to errors and low academic achievement for students. Authentic assessment methods require students to construct responses through the critical analysis of information presented in real-world contexts. Hence, this research investigated the difference in seafarer students' academic achievement (measured through scores obtained in assessment) in authentic assessment as compared with traditional assessment. Two separate and independent student groups (the ‘control’ group and ‘treatment’ group) were used for a selected unit of learning delivered at the Australian Maritime College within the Bachelor of Nautical Science degree program. Because some past researchers had defined and implemented traditional assessment methods as a single-occasion assessment, this project implemented the assessment in a summative format, as opposed to authentic assessments implemented during student preparation. Analysis of student scores revealed that the authentically assessed students were guided towards significantly higher academic achievement.

Most previous research has handled the task of ship type recognition by exploring hand-craft ship features, which may fail to distinguish ships with similar visual appearances. This situation motivates us to propose a novel deep learning based ship type recognition framework which we have named coarse-to-fine cascaded convolution neural network (CFCCNN). First, the proposed CFCCNN framework formats the input training ship images and data, and provides trainable input data for the hidden layers of the CFCCNN. Second, the coarse and fine steps are run in a nesting manner to explore discriminative features for different ship types. More specifically, the coarse step is trained in a similar manner to the traditional convolution neural network, while the fine step introduces regularisation mechanisms to extract more intrinsic ship features, and fine tunes parameter settings to obtain better recognition performance. Finally, we evaluate the performance of the CFCCNN model for recognising the most common types of merchant ship (oil tanker, container, LNG tanker, chemical carrier, general cargo, bulk carrier, etc.). The experimental results show that the proposed framework obtains better recognition performance than the conventional methods of ship type recognition.

A ship's grounding appears to be a significant threat to the safety of its crew, marine environment and the local ports economy. The risk of such incidents is higher in rivers since weather conditions can significantly alter the depths of channels from those shown on navigation charts. By means of a fuzzy analytic hierarchy process, a new methodology is proposed, capable of evaluating the hazards of a ship's grounding in a river. The proposed method contributes to safe navigation in rivers. Navigators are able to assess grounding risk in a river passage based on local information of past incidents. The proposed methodology is used to evaluate commercial risks from groundings in the Parana River. A case study was carried out using data from 118 cases, as provided by local agencies for the period 2008–2017.

The main objective of the European Geostationary Navigation Overlay System (EGNOS) is to improve the positioning accuracy by correcting several error sources affecting the Global Positioning System (GPS) and to provide integrity information to GPS signals for users in real time. This research presents analysis used to investigate improvement in the performance of single-frequency GPS positioning using EGNOS corrections in Algeria. In this study, we performed position measurements with two calculation approaches, the first based on GPS single-point positioning and the second using EGNOS differential corrections. Positioning accuracy was determined by comparison with the known precise coordinates of the sites; and then the improved ionospheric correction using EGNOS was investigated. The results revealed that GPS + EGNOS performance was significantly improved compared with GPS alone, when measurements of horizontal and vertical accuracy were taken into account, and that the EGNOS corrections improved east and north components slightly, and the up component significantly.

In the first aerial crossing of the South Atlantic, by Gago Coutinho and Sacadura Cabral in 1922, several methods of astronomical maritime navigation were used with adaptions to aerial navigation. In order to apply these methods, the navigator needed to know the approximate altitude of the aircraft so that its position could be determined. The instrument available at that time, the altimeter, did not give reliable values for altitude. Therefore, Coutinho had to devise a method that enabled the navigator to determine the altitude quickly and efficiently. The method Coutinho devised is based on a mathematical and geometrical procedure. In this paper, we study in detail Coutinho's method to determine altitude, with diagrams to aid understanding of the deductions and calculations. We also present a real example of how this method would be used during the flight.

A distributed four-dimensional (4D) trajectory generation method based on multi-agent Q learning is presented for multiple unmanned aerial vehicles (UAVs). Based on this method, each vehicle can intelligently generate collision-free 4D trajectories for time-constrained cooperative flight tasks. For a single UAV, the 4D trajectory is generated by the bionic improved tau gravity guidance strategy, which can synchronously guide the position and velocity to the desired values at the arrival time. Furthermore, to optimise trajectory parameters, the continuous state and action wire fitting neural network Q (WFNNQ) learning method is applied. For multi-UAV applications, the learning is organised by the win or learn fast-policy hill climbing (WoLF-PHC) algorithm. Dynamic simulation results show that the proposed method can efficiently provide 4D trajectories for the multi-UAV system in challenging simultaneous arrival tasks, and the fully trained method can be used in similar trajectory generation scenarios.

The presence of code Doppler and navigation bit sign transitions means that the acquisition of global positioning system (GPS) signals is difficult in weak signal environments where the output signal-to-noise ratio (SNR) is significantly reduced. Post-correlation techniques are typically utilised to solve these problems. Despite the advantages of these techniques, the post-correlation techniques suffer from problems caused by the code Doppler and the navigation bit sign transitions. We present an improved semi-bit differential acquisition method which can improve the code Doppler and the bit sign transition issues in the post-correlation techniques. In order to overcome the phenomenon of navigation bit sign transitions, the proposed method utilises the properties of the navigation bit. Since each navigation bit takes as long as 20 ms, there would be 10 ms correlations duration integration time between the received signal and the local coarse/acquisition (C/A) code in which the navigation bit sign transitions will not occur. Consequently, this problem can be cancelled by performing 10 ms correlations in even and odd units separately. Compensation of the code Doppler is also accomplished by shifting the code phase of the correlation results. To validate the performance of our suggested method, simulations are performed based on three data sets. The results show that the quantity of required input SNR to detect at least four satellites in the proposed method is − 48·3 dB, compared with − 20 dB and − 9 dB, respectively, in traditional differential and non-coherent methods.

This work quantitatively analyses vessel traffic service (VTS) communications in ports and suggests improvements for more efficient control of the service. For this purpose, analysis of VTS communications was performed on VHF channel 12 in Busan North Port, South Korea. This communications service follows the queue of M/G/1 (the arrivals have a Poisson distribution, the service time is characterized by a general distribution, and with a single server). The degree of congestion of the communication channel was shown as the utilisation rate of the queue, which was 67·7% at peak times and 29·6% at non-peak times. To reduce congestion in the communication channel, we propose to separate the peak time control channel, exclude passing reporting, and decrease the reporting time. With separation of the peak time control channel, the utilisation rate decreased by 41·1%. The utilisation rate decreased by 5·7% when passing reporting was omitted, and by 8·3% when reporting time was reduced by 60%. The results of this study can be used as basic policy data to improve VTS, including reinforcement of the VTS officer's role and adjustment of the control report contents.

With more and more missions around the Moon, a communication/navigation constellation around the Moon is necessary. Halo orbits, due to their unique geometry, are extensively studied by researchers for this purpose. A dedicated survey is carried out in this work to analyse the coverage ability of halo orbits. It is found that a two-satellite constellation is enough for continuous one-fold coverage of the north or the south polar regions but never both. A three-satellite constellation is enough for continuous one-fold coverage of both north and south polar regions. A four-satellite constellation can cover nearly 100% of the whole lunar surface. In addition, the coverage ability of another special orbit – distant retrograde orbit (DRO) – is analysed for the first time in this study. It is found that three satellites on DROs can cover 99·8% of the lunar surface, with coverage gaps at polar caps. A four-satellite constellation moving on spatial DROs can cover nearly the whole lunar surface. By combining halo orbits and DROs, we design a five-satellite constellation composed of three halo orbit satellites and two DRO satellites. This constellation can provide 100% continuous one-fold coverage of the whole lunar surface.

In the process of composing a double-differenced positioning model, it is difficult to separate different frequency signals between code division multiple access (CDMA) systems, the single-difference ambiguity of the pivot satellite and phase differential inter-system biases (PDISBs). Hence it is difficult to calibrate in advance the bias between systems in order to build an inter-system model which only needs one pivot satellite. Based on analysis of the stability of PDISB parameters for non-overlapping frequency CDMA systems, this study adopts a particle filter to estimate the fractional part of the PDISBs (F-PDISBs) between the systems and proposes a particle filter-based inter-system positioning model. Results show that the F-PDISBs and code DISBs for the baselines with the same receiver types and some with different receiver types are rather stable over time and for these baselines it is feasible to use a particle filter to estimate the F-PDISB parameters in the initial stage. Having attained the F-PDISBs, the inter-system model can be constructed to improve positioning accuracy in complex operational environments.