Synchronisation of the received Pseudorandom (PRN) code and its locally generated replica is fundamental when estimating user position in Global Navigation Satellite System (GNSS) receivers. It has been observed through experiments that user position accuracy decreases if sampling frequency is an integer multiple of the nominal code rate. This paper provides an accuracy analysis based on the number of samples and the residual code phase of each code chip. The outcomes reveal that the distribution of residual code phases in the code phase range [0, 1/ns), where ns is the number of samples per code chip, is the root cause of accuracy degradation, rather than the ratio between sampling frequency and nominal code rate. Doppler frequencies, coherent integration periods, front-end filter bandwidths and received Carrier to Noise ratios (C/N0) also influence receiver accuracy. Also provided are a sampling frequency selection guideline and new proposed estimates of the correlation output and the Delay Locked Loop (DLL) tracking error, which can be applied to precisely model GNSS receiver baseband signal processing.

We present a method of teaching the basics of celestial navigation, using the Javascript programming interface to Google Maps. This offers the teacher of celestial navigation many highly visual and flexible investigative and presentation options, all using the familiar Google Map system. In this paper, we discuss the programming route to Google Maps, and demonstrate an exercise of correcting the assumed position of a hypothetical lost ship, using sights of the Sun, suitable for classroom use. We also present an analysis of the relationship between the proximity of the assumed to the actual position of the ship, and the outcome of a sight-reduction procedure.

The demand for accurate indoor positioning continues to grow but the predominant positioning technologies such as Global Navigation Satellite Systems (GNSS) are not suitable for indoor environments due to multipath effects and Non-Line-Of-Sight (NLOS) conditions. This paper presents a new indoor positioning system using artificial encoded magnetic fields, which has good properties for NLOS conditions and fewer multipath effects. The encoded magnetic fields are generated by multiple beacons; each beacon periodically generates unique magnetic field sequences, which consist of a gold code sequence and a beacon location sequence. The position of an object can be determined with measurements from a tri-axial magnetometer using a three-step method: performing time synchronisation between sensor and beacons, identifying the beacon field and the beacon location, and estimating the position of the object. The results of the simulation and experiment show that the proposed system is capable of achieving Two-Dimensional (2D) and Three-Dimensional (3D) accuracy at sub-decimetre and decimetre levels, respectively.

This paper discusses the estimation algorithms for Three-Dimensional (3D) displacement and 3D rotation using Two-Dimensional (2D) laser scanners. An efficient outlier detection method is proposed for both algorithms to help protect the integrity of navigation. The algorithms have been evaluated using both simulation and field test results. They are able to produce a robust odometry solution for an autonomous aircraft in an indoor environment.

The integration of multi-constellation Global Navigation Satellite System (GNSS) measurements can effectively improve the accuracy and reliability of navigation and positioning solutions, while the Inter-System Bias (ISB) is a key issue for compatibility. The ISB is traditionally estimated as an unknown parameter along with three-dimensional position coordinates and a receiver clock offset with respect to Global Positioning System (GPS) time. ISB estimation of this sort will sacrifice a satellite observation for each integrated GNSS system. These sacrificed observations could be vital in situations of limited satellite visibility. In this study, an enhanced multi-GNSS navigation algorithm is developed to avoid sacrificing observations under poor visibility conditions. The main idea of this algorithm is to employ a moving average filter to smooth the ISBs estimated at previous epochs. The filtered value is utilised as a priori information at the current epoch. Experimental tests were conducted to evaluate the enhanced algorithm under open and blocked sky conditions. The results show that the enhanced algorithm effectively improves the accuracy and availability of navigation solutions under the blocked sky condition, with performance being comparable to traditional ISB estimation algorithms in open sky conditions. The improvement rates of the three-dimensional position accuracy and availability reach up to 63% and 21% in the blocked sky environment. Even in the case of only four different GNSS satellites, a position solution can still be obtained using the enhanced algorithm.

With the improvement of the bias instability of Micro-Electromechanical Systems (MEMS) gyroscopes, the g-sensitivity error is gradually becoming one of the more important factors that affects the dynamic accuracy of a MEMS gyroscope. Hence there is a need for correcting the g-sensitivity error. However, the traditional calibration of g-sensitivity error uses a centrifuge. The calibration conditions are harsh, the process is complex and the cost is relatively high. In this paper, a fast and simple method of g-sensitivity error calibration for MEMS gyroscopes is proposed. With respect to the bias and random noise of a MEMS gyroscope, the g-sensitivity error magnitude is relatively small and it is simultaneously coupled with the Earth's rotation rate. Therefore, in order to correct the g-sensitivity error, this work models the calibration for g-sensitivity error coefficients, designs an (8+N)-position calibration scheme, and then proposes a fitting method for g-sensitivity error coefficients based on the Newton iteration and least squares methods. Multi-group calibration experiments designed on a MEMS Inertial Measurement Unit (MEMS IMU) product demonstrate that the proposed method can calibrate g-sensitivity error coefficients and correct the g-sensitivity error effectively and simply.

A better understanding of passenger movement in multi-modal transit situations is the major aim of this study. By using a novel Cooperative Positioning (CP) approach, algorithms can be generated which considerably increase the accuracy of person tracking. Smooth transit at stations is enabled, thus the total waiting time for routing at the traffic interchange is reduced. A Location-Based Services (LBS) user is guided by the service and located with the assistance of the whole user group. In addition to the technological developments, the acceptance and end-user needs are considered. End-users of such a service have the right to withdraw their consent for transferring location-based and other personal data at any time. They also receive clear and comprehensive information about when and why they reveal their personal data and location and its further use. In this paper, the concept is introduced followed by a comprehensive discussion of the suitable CP localisation techniques as well as an implementation strategy. Furthermore, ethical and usability aspects are discussed to ensure user-friendly results.

The objective of this paper is to accurately determine mobile robots' position and orientation by integrating information received from odometry and an inertial sensor. The position and orientation provided by odometry are subject to different types of errors. To improve the odometry, an inertial measurement unit is exploited to give more reliable attitude information. However, the nonlinear dynamic of these systems and their complexities such as different sources of errors make navigation difficult. Since the dynamic models of navigation systems are nonlinear in practice, in this study, a Cubature Kalman Filter (CKF) has been proposed to estimate and correct the errors of these systems. The information from odometry and a gyroscope are integrated using a CKF. Simulation results are provided to illustrate the superiority and the higher reliability of the proposed approach in comparison with conventional nonlinear filtering algorithms such as an Extended Kalman Filter (EKF).

The current positioning accuracy of the BeiDou Navigation Satellite System (BDS) Single Point Positioning (SPP) with code measurement is in the order of several metres due to systematic errors. To further reduce the systematic errors in SPP, this contribution develops a new strategy to BDS SPP with a sparse reference network, named Augmented SPP (A-SPP). In this method, the Combined Residual Errors (CRE) products of BDS B1I measurement are integrated with three optional base stations that are close to the rover station. Based on the Satellite Elevation Angle Weighted (SEAW) average technique, the code residual errors of each BDS satellite observed by the rover station can be acquired epoch-by-epoch. Finally, the corrected code observations for the rover station can be utilised to achieve an A-SPP solution. The validation of this method is confirmed by both static and kinematic tests. Results clearly show that the accuracies of the A-SPP solution for horizontal and vertical directions are better than 0·5 m and 1·0 m. This study suggests that the proposed A-SPP solution is a good option for single-frequency GNSS users to improve their positioning performance.

Marine accident analysis is important for ships passing through narrow, shallow and busy waterways. This study analyses the accidents which have occurred in the Istanbul Strait and proposes both quantitative and qualitative assessments of marine accidents. Marine accidents occurring in the Istanbul Strait are analysed by using a method based on neuro-fuzzy and genetically optimised fuzzy classifiers. It can be concluded that accident severity increases when poor weather conditions prevail in the Strait regardless of ship size. Therefore, solutions to reduce unwanted events should be prioritised by accounting for weather conditions and the capacity of the vessels. This analysis indicates that the safety level would be significantly improved if all the vessels follow the passage guidelines.

Increasing the stability and reliability of navigation for mobile objects of different classes is becoming increasingly significant. Satellite navigation systems have a fundamental defect: a vulnerability to hacking and spoofing. Observation of the horizon line is significant for two applications. The first is stellar inertial navigation systems. In this case, the horizon line can be used for local vertical estimation. Errors in local vertical estimation directly affect coordinate errors. The second is correlation-extremal navigation based on the observed horizon line shape (when islands or continents are observed from aerial vehicles). In both cases, instability of the horizon line produces navigation errors. A measurement procedure for horizon line position estimation was proposed and realised. Around-the-clock horizon line shooting was undertaken in 2013. Processing of the results shows a horizon line direction instability of about 5–7 angular minutes during the day time.

The basis of all recommended methods for obtaining position by using celestial bodies is the known altitude of the celestial body being observed. Accordingly, it is necessary to have a sextant, classic or with an artificial horizon, or some other device that can measure altitude. However, there is a way to obtain position using astronomical navigation without determining the altitude of a celestial body, and this method will be analysed in this paper. The introduced method requires only precise measurement of the azimuth, and is based on determining two positions close to the dead reckoning position and lying on the isoazimuthal curve, i.e. a curve of the same great circle azimuths of a celestial body. Furthermore, the model assumes that a part of this curve, between the selected positions, can be replaced by a straight line. Special attention will be given to the analysis of errors of the line of position for various azimuth errors and various dead reckoning (assumed) positions. It will also be shown how a modern Electronic Chart Display and Information System (ECDIS) can help in approximate position determination, knowing only the azimuths of celestial bodies.

The Micro-Nano satellite TianTuo-3 (TT-3) developed by the National University of Defense Technology (NUDT) was successfully launched on 20 September 2015. The space-based Automatic Identification System (AIS) on board TT-3 works well and stably receives AIS signals from global vessels. In this work, we perform statistical analysis on the detection probability of the vessels in the concerned areas by using the TT-3 AIS data. The results suggest that the detection probability of vessels decreases as the distribution density increases, especially in the offshore areas of dense traffic and the TT3-AIS vessel detection probability in the oceans can be higher than 40%, indicating that the TT-3 AIS has achieved a high probability of coverage of vessels for a single receiving antenna. The analysis results will present helpful references both in evaluating the potential application of satellite-based AIS and for designing the next generation space-based AIS which might greatly improve the detection probability of ocean-going vessels.

For multi-Autonomous Underwater Vehicle (multi-AUV) system task assignment and path planning, a novel Glasius Bio-inspired Self-Organising Map (GBSOM) neural networks algorithm is proposed to solve relevant problems in a Three-Dimensional (3D) grid map. Firstly, a 3D Glasius Bio-inspired Neural Network (GBNN) model is established to represent the 3D underwater working environment. Using this model, the strength of neural activity is calculated at each node within the GBNN. Secondly, a Self-Organising Map (SOM) neural network is used to assign the targets to a set of AUVs and determine the order of the AUVs to access the target point. Finally, according to the magnitude of the neuron activity in the GBNN, the next AUV target point can be autonomously planned when the task assignment is completed. By repeating the above three steps, access to all target points is completed. Simulation and comparison studies are presented to demonstrate that the proposed algorithm can overcome the speed jump problem of SOM algorithms and path planning in the 3D underwater environments with static or dynamic obstacles.

This paper describes George Biddell Airy's almost completely unknown method of approximating an orthodromic arc (great circle arc) using a circular arc in the normal aspect Mercator projection of a sphere. In addition, it is demonstrated that the centre of the circle can be defined in at least two different ways, which yields slightly different results. Airy's approach is built upon in this paper. The method of computing coordinates of Airy's circle arc centre is described. The formulae derived in the paper can be used to calculate the length of Airy's approximation of the orthodromic arc connecting two points on the sphere and on the Mercator chart. Moreover, the actual length of the orthodromic arc on the sphere and on the Mercator chart can be computed using the formulae derived in this paper. The purpose of the paper is not to suggest an application of Airy's method in navigation, but to analyse Airy's proposal and to show that a great circle arc on a Mercator chart is close to a circular arc for distances which are not too great. This property can be useful in education, having in mind that the stereographic projection is the only one that maps any circle on a sphere onto a circle in the projection plane.

We examine the relation between fix error and the azimuthal distribution of lines of position by subsuming the distribution into a scalar form Q analogous to the nematic order parameter of statistical physics. It is shown in the least-squares approach that the error behaves as (1−Q2)−1/2. Simulation results are presented to demonstrate the control of Q as a strategy for fix improvement.