In view of the shortcomings of existing satellite navigation systems in deep-space performance, candidate architectures which utilise libration point orbits in the Earth-Moon system are proposed to create an autonomous satellite navigation system for lunar missions. Three candidate constellations are systematically studied in order to achieve continuous global coverage for lunar orbits: the Earth-Moon L1,2 two-satellite constellation, the Earth-Moon L2,4,5 three-satellite constellation and the Earth-Moon L1,2,4,5 four-satellite constellation. After a thorough search for possible configurations, the latter two constellations are found to be the simplest feasible architectures for lunar navigation. Finally, an autonomous orbit determination simulation is performed to verify the autonomy of the system and two optimal configurations are obtained in a comprehensive consideration of coverage and autonomous orbit determination performance.

The advent of multiple Global Navigation Satellite System (GNSS) constellations will result in a considerable increase in the number of satellites for positioning worldwide. This substantial improvement in measurement redundancy has the potential to radically advance receiver autonomous integrity monitoring (RAIM) performance. However, regardless of the number of satellites, the performance of existing RAIM methods is sensitive to the assumed prior probabilities of individual fault hypotheses. In this paper, a new method is developed using Bayes’ theorem to generate upper bounds on posterior probabilities of individual fault hypotheses given current user measurements. These bounds are used in a Bayesian fault-tolerant position estimator (FTE) that minimizes integrity risk. The detection test statistic is a measurement-based integrity risk bound, which is directly compared with a pre-specified risk requirement. The associated challenge of quantifying continuity risk is resolved using a bounding approach, which is also detailed in this work. The new Bayesian FTE method is shown to be more robust to uncertainty in prior probability of fault occurrence than existing RAIM methods.

To eliminate the impact of the Doppler effects caused by the motion of the Mars explorer, a novel X-ray pulsar navigation method based on a closed-loop filter is proposed. In the pulsar signal observation period, the Doppler velocity predicted by the orbit dynamic model and the prior information is utilised to compensate the X-ray photon time-of-arrival (TOA). However, because of the error in prior information, there is a bias caused by the Doppler compensation in the pulse time-of-arrival. The pulse TOA bias and the Mars explorer's state estimation error are correlated, which results in the decline of the Kalman filter performance. To deal with this problem, we build the TOA measurement model with respect to the state estimation error, and utilise the closed-loop extended Kalman filter (EKF) as the navigation filter, where the predicted state error is adopted as the state estimation. The simulation results demonstrate the feasibility, real-timeliness and effectiveness of the proposed navigation method. The navigation method based on the closed-loop EKF using the measurement model with the Doppler effects is more accurate than the traditional one.

AIS was primarily developed to exchange vessel-related data among vessels or AIS stations by using very-high frequency (VHF) technology to increase safety at sea. This study evaluates the formal integrity, availability, and the reporting intervals of AIS data with a focus on vessel movement prediction. In contrast to former studies, this study is based on a large data collection of over 85 million AIS messages, which were continuously received within a time period of two months. Thus, the evaluated data represent a comprehensive and up-to-date view of the current usage of AIS systems installed on vessels. Results of previous studies concerning the availability of AIS data are confirmed and extended. New aspects such as reporting intervals are additionally evaluated. Received messages are stored in a database, which allows for performing database queries to evaluate the obtained data in an automatic way. This study shows that almost ten years after becoming mandatory for professional operating vessels, AIS still lacks availability for both static and dynamic data and that the reporting intervals are not as reliable as specified within the technical AIS standard.

With the availability of Galileo signals from four in-orbit validation (IOV) satellites, positioning with Galileo-only observations has become possible, which allows us to assess its positioning performance. The performance of the Galileo system is evaluated in respect of carrier-to-noise density ratio (C/N0), pseudorange multipath (including noise), Galileo broadcast satellite orbit and satellite clock errors, and single point positioning (SPP) accuracy in Galileo-only mode as well as in GPS/Galileo combined mode. The precision of the broadcast ephemeris data is assessed using the precise satellite orbit and clock products from the Institute of Astronomical and Physical Geodesy of the Technische Universität München (IAPG/TUM) as references. The GPS-Galileo time offset (GGTO) is estimated using datasets from different types of GNSS receivers and the results indicate that a systematic bias exists between different receiver types. Positioning solutions indicate that Galileo-only SPP can achieve a three-dimensional position accuracy of about six metres. The integration of Galileo and GPS data can improve the positioning accuracies by about 10% in the vertical components compared with GPS-only solutions.

An innovative algorithm to determine the inverse solution of a geodesic with the vertex or Clairaut constant located between two points on a spheroid is presented. This solution to the inverse problem will be useful for solving problems in navigation as well as geodesy. The algorithm to be described derives from a series expansion that replaces integrals for distance and longitude, while avoiding reliance on trigonometric functions. In addition, these series expansions are economical in terms of computational cost. For end points located at each side of a vertex, certain numerical difficulties arise. A finite difference method together with an innovative method of iteration that approximates Newton's method is presented which overcomes these shortcomings encountered for nearly antipodal regions. The method provided here, which does not involve an auxiliary sphere, was aided by the Computer Algebra System (CAS) that can yield arbitrarily truncated series suitable to the users accuracy objectives and which are limited only by machine precisions.

Currently, the 30 nautical mile (nm) minimum longitudinal separation standard is applied on oceanic routes under the Automatic Dependent Surveillance-Contract (ADS-C) environment. However, the periodic position report should be provided at least every ten minutes in Japanese airspace based on previous safety analysis. The position report is usually sent via satellite connection, so less frequent position reports would reduce connection costs by airlines. Since the previous safety analysis estimates the risk of collision conservatively, this paper proposes a refinement of the collision risk model by considering the dependency between two closely separated aircraft. The result shows that the periodic position report interval can be extended without infringing safety.

The complementary advantages of high-rate Global Positioning System (GPS) and accelerometer observations for measuring seismic ground motion have been recognised in previous research. Here we propose an approach of tight integration of GPS and accelerometer measurements. The baseline shifts of the accelerometer are introduced as unknown parameters and estimated by a random walk process in the Precise Point Positioning (PPP) solution. To demonstrate the performance of the new strategy, we carried out several experiments using collocated GPS and accelerometer. The experimental results show that the baseline shifts of the accelerometer are automatically corrected, and high precision coseismic information of strong ground motion can be obtained in real-time. Additionally, the convergence and precision of the PPP is improved by the combined solution.

The accuracy of attitude determination using a star sensor tends to be degraded if the host vehicle's manoeuvring smears the star image. In this paper, a new restoration algorithm with the aid of a Strap-down Inertial Navigation System (SINS) is proposed to reduce the effect of the smeared image. The smeared trace length is estimated with aid of the SINS angular rate. The restoration algorithm based on a Wiener filter is designed after the smeared zone is derived with the aid of the SINS coarse attitude. A tracking method is proposed to reject the stars of low centroid extraction accuracy. Simulations demonstrate that the success rate and the accuracy of attitude determination are improved significantly by the restoration algorithm even under a very fast rotation. The impact of the SINS error on the restoration is evaluated in the simulations.

This paper presents a new algorithm to accelerate Precise Point Positioning (PPP) convergence. The main idea is to consider the station tropospheric zenith total delay, which is obtained by a global zenith troposphere delay estimate model, as virtual observation and combine it with phase and pseudo-range observations to formulate observation equations. Without relying on any other external enhancement information, it only requires four satellites to quickly complete the positioning with centimetre-level accuracy. Compared with the conventional method, the new one brings about 15% improvement in convergence time.

The BeiDou system has been providing a regional navigation service since 27 December 2012. The Global Navigation Satellite System (GNSS) user community will benefit from combined Global Positioning System (GPS)/BeiDou positioning due to improved positioning accuracy, reliability and availability. But to achieve the best positioning solutions, precise weights of the GPS and BeiDou observations are important since this involves the processing of measurements from two different satellite systems with different quality. Currently, a priori variances are typically used to determine the weights of different types of observations. However, such an approach may not be precise since many un-modelled errors are not accounted for. The Helmert variance component estimation method is more appropriate in this case to determine the weights of GPS and BeiDou observations. This requires high redundant observations in order to obtain reliable solutions, which will be a concern in the case of insufficient numbers of visible satellites. To address this issue, a weighting approach is proposed by a combination of the Helmert method and a moving-window average filter. In this approach, the filter is applied to combine all epoch-by-epoch weight estimates within a time window. As a result, more precise and reliable weights for GPS and BeiDou observations can be obtained at every epoch. Both static and kinematic tests in open sky and under tree environments are conducted to assess the performance of the new weighting approach. The results indicate significantly improved positioning accuracy.