Finding one's geographical position (fix) without the use of a Global Navigation Satellite System (GNSS), which was common place before the establishment of the latter, could be tedious and/or inaccurate. Apart from sound knowledge of spherical trigonometry and navigational methods, it also requires the knowledge of the navigator's approximate or assumed position, the use of the current year's celestial bodies' ephemeris (Nautical Almanac), and graphical methods (Lines of Position – LOP) which sometimes can prove wanting in accuracy and/or challenging for the unaccustomed user. The method proposed here is based on sight reduction from two celestial bodies, and directly calculates the geographical position, both for stationary and moving observers (“running fix”) using easily available modern programmable calculating devices, without the need of the assumed position, graphical methods (LOP) or the current year's ephemeris, hence the term “stand-alone”. This self-contained method is implemented by the author in a software application, which can be easily used in a portable computer (for example, a smartphone). The results are considered satisfactorily accurate.

This paper outlines the results of a project to develop and test an augmented reality smart phone application (‘app’) to aid the safety of navigation of leisure sailors with limited navigational skills. The app works in two modes: in the ‘turned off mode’ the app gives an alarm 30 seconds before the boat is predicted to ground. The navigator then immediately stops the boat, picks up the phone and, uses the app to view the surrounding water where NoGo areas less than 3 metres in depth are outlined in red. By panning the smart phone around, safe escape routes with deep water are visible. The prototype app was tested on a group of boat owners in western Norway with very good results, both from technical and usability perspectives. This report outlines the concept of operation of the app, details some of the difficulties encountered in its development and testing, specifies the issues that remain to be resolved to turn the concept into an effective system, and outlines future development plans.

This paper presents a binocular vision-IMU (Inertial Measurement Unit) tightly-coupled structure based on a Minimum sigma set Square-Root Unscented Kalman Filter (M-SRUKF) for real time navigation applications. Though the M-SRUKF has only half the sigma points of the SRUKF, it has the same accuracy as the SRUKF when applied to the binocular vision-IMU tightly-coupled system. As the Kalman filter flow is a kind of square-root system, the stability of the system can be guaranteed. The measurement model and the outlier rejection model of this tightly-coupled system not only utilises the epipolar constraint and the trifocal tensor geometry constraint between the consecutive two image pairs, but also uses the quadrifocal tensor geometry among four views. The structure of the binocular vision-IMU tightly-coupled system is in the form of an error state, and the time updates of the state and the state covariance are directly estimated without using Unscented Transformation (UT). Experiments are carried out based on an outdoor land vehicle open source dataset and an indoor Micro Aerial Vehicle (MAV) open source dataset. Results clearly show the effectiveness of the proposed new mechanisation.

To satisfy the needs of precise pin-point landing missions in deep space exploration, this paper proposes a method based on feature line extraction and matching to estimate the attitude and position of a lander during the descent phase. Linear equations for a lander's motion parameters are given by using at least three feature lines on the planetary surface and their two-dimensional projections. Then, by taking advantage of Singular Value Decomposition (SVD), candidate solutions are obtained. Lastly, the unique lander's attitude and position relative to the landing site are selected from the candidate solutions. Simulation results show that the proposed algorithm is able to estimate a lander's attitude and position robustly and quickly. Without an extended Kalman filter, the average errors of attitude are less than 1° and the average errors of position are less than 10 m at an altitude of 2,000 m. With an extended Kalman filter, attitude errors are within 0·5° and position errors are within 1 m at an altitude of 247·9 m.

High-precision underwater positioning must eliminate the influence of refraction artefacts. Since a Time Of Arrival - Global Navigation Satellite System Intelligent Buoys (TOA-GIB) system does not measure incident beam angles, common refraction correction methods cannot be directly used for refraction artefacts. An Equivalent Sound Speed (ESS) iteration method is proposed and is based on the transformation relations between depth, the ESS gradient and the incident beam angle. On this basis, a TOA/AOA-GIB system without a real-time Sound Speed Profile (SSP) is proposed to estimate the target position and the ESS gradient as unknown parameters. The results from a simulation experiment show that the positioning accuracy of a TOA/AOA-GIB system is better than 0·07% of water depth when the accuracy of the incident beam angle is 0·1°.

A Rotational Inertial Navigation System (RINS) redundant configuration is commonly adopted in high-accuracy marine navigation. Single-axis RINS and dual-axis RINS redundant configurations are good choices with single-axis RINS being a hot backup system, and are trade-offs between position accuracy, reliability as well as cost. However, lack of information fusion between systems is common. Therefore, a novel navigation information fusion method based on an augmented error state Kalman filter is proposed for a RINS redundant configuration. The azimuth gyro drift of a single-axis RINS whose influence cannot be averaged out by single-axis rotation can be estimated, whereby the deterministic position error can be predicted and compensated. Hence, the position accuracy in the event of dual-axis RINS failure can be guaranteed by improving the performance of a single-axis RINS. In addition, an online performance evaluation method is proposed to select the better performance dual-axis RINS as master RINS in a triple RINS configuration, including two sets of dual-axis RINS and a single-axis RINS, which is used in some particularly high reliability applications. Semi-physical simulations and experiments show the proposed method works well.

General Aviation (GA) pilots need, more than ever, to be constantly aware of their aircraft's position especially when they navigate in areas surrounded by controlled airspace. With pilots being taught to navigate using visual landmarks and radio, the increasing use of space-based navigation aids might degrade the pilot's performance. Given limited literature resources on navigation by GA pilots, the following three navigation methods are outlined: visual, radio-based and space-based navigation. 27 GA pilots were interviewed in three European nations to determine the navigation methods currently used and their impact on the pilots’ performance. The selection of the participants based on aircraft type (fixed-wing, ultralight and glider), in three European nations highlights profound differences in navigation between the three most popular aircraft designs. Furthermore, space-based navigation aids, in particular portable computers, have changed both planning and navigation implying that changes in the training of pilots are urgently needed to enhance the pilot's performance, and subsequently, to promote aviation safety.

A novel fast adaptive-gain complementary filter algorithm is developed for Unmanned Aerial Vehicle (UAV) attitude estimation. This approach provides an accurate, robust and simple method for attitude estimation with minimised attitude errors and reduced computation. UAV attitude data retrieved from accelerometer data is transformed to the solution of a linearly discrete dynamic system. A novel complementary filter is designed to fuse accelerometer and gyroscope data, with a self-adjusted gain to achieve a good performance in accuracy. The performance of the proposed algorithm is compared with an Adaptive-gain Complementary Filter (ACF) and Extended Kalman Filtering (EKF). Simulation and experimental results show that the accuracy of the proposed filter has the same performance as an EKF in high dynamic operating conditions. Therefore, the proposed algorithm can balance accuracy and time consumption, and it has a better price/performance ratio in engineering applications.

An interplanetary autonomous navigation network, named the Internet of Spacecraft (IoS), is proposed in this paper to enable a Solar System-wide autonomous navigation capability for spacecraft. This network consists of two types of spacecraft, namely host and client spacecraft. The former provide the absolute reference for the whole network, and the latter determine their positions by communicating with the host spacecraft or other client spacecraft. To investigate the performance of IoS, a detailed application scheme that supports a flight from Earth to Mars is developed and analysed. IoS is not a simple extension of the navigation constellation. It is independent of the ground tracking system and the configuration of the network is flexible in that any spacecraft-installed identical device can be added to it. Moreover, client spacecraft whose positions have been determined can also be regarded as host spacecraft and provide further navigation information to others. This paper aims to provide technical support for future deep space exploration.

This paper proposes a dynamic aided inertial navigation method to improve the attitude accuracy for ocean vehicles. The proposed method includes a dynamic identification algorithm and the utilisation of dynamic constraints to derive additional observations. The derived additional observations are used to update the filters and limit the attitude error based on the dynamic knowledge. In this paper, two dynamic conditions, constant speed cruise and quasi-static, are identified and corresponding additional velocity and position observations are derived. Simulation and experimental results show that the proposed method can improve and guarantee the accuracy of the attitude. The method can be used as a backup method to bridge external information outages or unavailability. Both the features of independence of external support and integrity of the Inertial Navigation System (INS) are enhanced.

Tactical monitoring and controlling of air traffic is becoming increasingly difficult to manage for Air Traffic Controllers (ATCOs) owing to an increasingly complex traffic flow. A dynamic tactical complexity model, herein known as Conflict Activity Level (CAL), has been developed and is presented in this paper. This can be achieved either by establishing an overall score for an entire region or sub-regions of interest as specified by user's input location and time. This is done by evaluating the likely aircraft flight shape profile based on its current and projected position and trajectory. From the flight shape profile, CAL values are computed based on instantaneous existing traffic numbers in the overall region or sub-regions of interest. The proposed complexity approach shows good agreement with other methods in terms of ranking the order of complexity of various air traffic scenarios and the key influencing factors contributing to conflict.

This paper proposes a simplified algorithm for reducing the computational load of the conventional underwater integrated navigation system. The system usually comprises a three-dimensional accelerometer, a three-dimensional gyroscope, a three-dimensional Doppler Velocity Log (DVL) and a data fusion algorithm, such as a Kalman Filter (KF). Since the expected variations of roll, pitch and depth are small, these quantities are assumed to be constant, and the proposed system is designed in a two-dimensional form. Due to the low speed of the vehicle, the nonlinear dynamic equation of the velocity can be simplified in a linear form. We also simplify the conventional KF in order to avoid matrix multiplications and matrix inversions. The performance of the designed system is evaluated in a sea trial by an Autonomous Underwater Vehicle (AUV). The results show that the proposed system can significantly reduce the computational load of the conventional integrated navigation system without a significant reduction in position and velocity accuracy.

Cycle slip detection for single frequency Global Navigation Satellite System (GNSS) data is currently mainly based on measurement modelling or prediction, which cannot be effectively performed for kinematic applications and it is difficult to detect or repair small cycle slips such as half-cycle slips. In this paper, a new method that is based on the total differential of ambiguity and Least-Squares Adjustment (LSA) for cycle slip detection and repair is introduced and validated. This method utilises only carrier-phase observations to build an ambiguity function. LSA is then conducted for detecting and repairing cycle slips, where the coordinate and cycle slips are obtained successively. The performance of this method is assessed through processing short and long baselines in static and kinematic modes and the impact of linearization and atmospheric errors are analysed at the same time under a controlled variable method. The results indicate this method is very effective and reliable in detecting and repairing multiple cycle slips, especially small cycle slips.

In this paper, both the proportional derivative feedback control and variable-structure sliding mode control approaches based on dual numbers are presented to design space flyaround and in-orbit inspection missions. Dual-number-based spacecraft kinematics and dynamics models are formulated. The integrated translational and rotational motions can be described in one compact expression, and the mutual coupling effect can be considered. A space flyaround and in-orbit inspection mission model based on dual numbers is derived. Both proportional derivative feedback control and variable-structure sliding mode control laws are designed using dual numbers. Simulation results indicate that both the proposed control system can provide high-precision control for relative position and attitude. Of the two systems, the variable-structure sliding mode control system performs the best.

Heading angle is a vital parameter in maintaining a vessel's track along a planned course and should be guaranteed in a stable and reliable way. An innovative method of heading determination based on a fisheye camera, which is almost totally unaffected by electromagnetism and geomagnetism, is proposed in this paper. In addition, unlike traditional astronomical methods, it also has a certain degree of adaptability to cloudy weather. Utilising the super wide Field Of View (FOV) of the camera, it is able to simultaneously image the Moon and the horizon. The Moon is treated as the observed celestial body and the horizon works as the horizontal datum. Two experiments were conducted at sea, successfully proving the feasibility of this method. The proposed heading determination system has the merits of automation, resistance to interference and could be miniaturised, making application viable.

As technology continues to develop, information and communication technology and operational technology on board ships are increasingly being networked, and more frequently connected to the Internet. The introduction of cyber systems changes the work environment with the aim of decreasing the workload for the navigator, but at the same time introduces more complexity and vulnerabilities that in turn may alter the competencies needed to perform safe and efficient navigation. Contemporary examples of how cyber-attacks can distort situational awareness and interfere with operations are needed to enhance the navigator's competence through increased system awareness. This paper demonstrates some of the possible attack vectors that a cyber-attack can present to a ship, as well as discussing the plausibility and consequences of such attacks. In this study we provide a practical example to better understand how one can demystify cyber threats in order to enhance the navigators' competence.

To track multiple ships and estimate the feature parameters of multiple emitters on board using electronic intelligence satellites under clutter interference, a long and random revisit time, and other complex conditions, a novel tracking algorithm using both kinematic (position and velocity) and feature information based on an improved Multiple Hypothesis Tracking (MHT) approach is proposed in this paper. Firstly, the characteristics of multi-ship tracking with multiple emitters using satellite electronic information are analysed, and a new model of an emitter is built as an extended target in geographical coordinates. Secondly, a pre-processing of measurements is utilised via hierarchical clustering using the location and feature information of emitters. Thirdly, feature information is incorporated into the MHT framework using Jensen-Shannon divergence distance and fuzzy C-means clustering to calculate track scores. Finally, we present the prediction and update of target states, especially the update of feature parameters, to realise joint kinematic and feature tracking of ships. The results of the simulation show that the proposed method has much better tracking performance than the standard MHT algorithm.