GPS receivers have been used successfully on low Earth orbit (LEO) satellite missions for several years. The use of a GPS receiver at altitudes higher than LEO, however, is non-trivial as the receiver will be outside the main lobe of the GPS broadcast signals, and it will have to track signals from GPS satellites transmitting from the other side of the Earth. This paper will review the special hardware and software adaptations required for GPS receiver operations on a medium Earth orbit or geostationary satellite, along with preliminary results from simulations and an in-orbit experiment.

This paper discusses the preliminary performance analysis result of the Asia-Pacific Global Navigation Satellite Systems (GNSS) Test Bed. Currently, seven Asia-Pacific economies are participating in the Test Bed project, namely Australia, Chinese Taipei, Indonesia, Malaysia, the Philippines, Thailand and Vietnam. The Test Bed was commissioned in May 2006. The discussion topics in this paper include Test Bed system architecture and preliminary analysis of the system performance. As presented in this paper, while current Satellite-Based Augmentation System (SBAS) algorithms can improve the accuracy performance of GPS positioning results, it cannot fulfill the integrity performance required by civil aviation community. This paper analyzes the limitation of the algorithm and proposes future research topics related to the limitation.

This paper examines the recent introduction of the AIS to the ship's bridge and its potential impact on the safety of marine navigation. Research has shown that 80 to 85% of all recorded maritime accidents are directly due to human error or associated with human error. Safety is an important element of marine navigation and many people at different levels are involved in its management. The safe and efficient performance of joint systems, is heavily dependent upon how functions are allocated between the human and the machine. This paper investigates different regulations, supervision for proper use, training, and management of AIS users. It uses previous research and three separate AIS studies to identify problems. The potential of the AIS to cause problems is analysed. The classic human factor “Swiss Cheese” Model of system failure has been modified for the AIS to investigate a possible accident trajectory. The paper then concludes with recommendations and suggestions for improvements and further work.

This paper introduces a “Personal Dead-reckoning” (PDR) navigation system for walking persons. The system is useful for monitoring the position of emergency responders inside buildings, where GPS is unavailable. The PDR system uses a six-axes Inertial Measurement Unit attached to the user's boot. The system's strength lies in the use of a technique known as Zero Velocity Update (ZUPT) that virtually eliminates the ill-effects of drift in the accelerometers. It works very well with different gaits, as well as on stairs, slopes, and generally on 3-dimensional terrain. The paper explains the PDR and presents extensive experimental results, which illustrate the utility and practicality of the system. Parts of this paper were presented at the 2006 International Joint Topical Meeting: “Sharing Solutions for Emergencies and Hazardous Environments,” February 12–15, 2006, Salt Lake City, Utah, USA.

The aim of the SPACE project is to develop a mobile test bed that can position to within centimetres in all conditions and environments. To achieve this goal, a number of different positioning technologies have to be integrated together including GNSS, INS, pseudolites and other technologies such as Ultra Wideband and Bluetooth ranging. The integration of these sensors is achieved by the development of a ‘plug and play’ filter that will optimally combine measurements from each sensor to form an accurate position solution. The filter has been designed so that the sensors are integrated at the measurement level wherever possible, so partial measurements from different systems can be used together.

This paper describes the development of the plug and play filter, focussing in particular on how the states are defined, how the measurements are used, and how a generic filter can be developed that can integrate all types of positioning sensor. Some early results from the filter are shown integrating GPS, INS and simulated measurements from an Ultra Wideband system. A prototype version of the mobile test bed is also described.

Satellite based navigation system integrity monitoring is essential both for liability and safety critical services. The threats to system integrity are the potential failure modes that could occur at system, operational and user sensor levels. Research on identification, characterisation and modelling of such failure modes, suggests that failures that grow slowly over time (e.g. ramp error less than 2 m/s), also referred to as slowly growing errors (SGE) are the most difficult to detect early. Conventional snapshot algorithms detect SGEs when the test statistic crosses the threshold usually after relatively long periods of time. A recent concept based on the average of residuals over time has been found to have a significant weakness. This paper proposes a “difference test” algorithm capable of detecting SGEs early. In this method, the test statistic is the difference between the norm of current residuals and the norm of the residuals at a previous epoch. The distribution of the test statistic is over-bounded by a normal distribution whose parameters are derived from two Chi-distributions. Results show that the new algorithm results in a significant reduction in detection time compared to conventional methods.

GPS applications such as Precise Point Positioning (PPP) require the availability of precise ephemeris at high rate. To support these applications, several institutions such as the International GNSS Service (IGS) have developed precise orbital service. Unfortunately, however, the data rate of such precise orbits is usually limited to 15 minutes. To overcome this problem, a number of orbital interpolation methods are proposed. This paper examines the performance of four interpolation methods for IGS precise GPS orbits, namely Lagrange, Newton Divided Difference, Cubic Spline and Trigonometric interpolation. In addition, the paper discusses a new approach, which utilizes the residuals between the broadcast and precise ephemeris to generate a high density precise ephemeris. It is shown that the new approach produces better results than previously reported orbital interpolation accuracy.

The modelling of most Global Navigation Satellite System (GNSS) errors/biases and developments of data processing techniques have been improved substantially since the birth of Global Positioning System (GPS), however, there has been much less progress in the improvement of phase multipath mitigation techniques. Multipath therefore remains one of the most important error sources in high precision GNSS positioning. This is because multipath is site-dependent and therefore cannot be eliminated by differencing techniques. Also multipath is highly dependent on satellite-reflector-antenna geometry, which usually causes rapid changes in phase multipath errors especially in Real-Time Kinematic (RTK) applications. Multipath mitigation for static antennas such as those at reference stations can be carried out by site calibration, averaging over long observation times, and through the estimation of the error using filtering based on signal-to-noise ratio (SNR) data. However, multipath mitigation for kinematic antennas is still very difficult today.

Nevertheless, much research has been carried out on a particular class of phase multipath mitigation techniques: ones that can be applied within positioning algorithms (rather than incorporated into the receiver tracking loops or antennas). This paper investigates and further develops a number of state-of-the-art techniques in this category. They include phase multipath estimation using SNR data, phase multipath estimation through the use of closely spaced antennas, multipath mitigation stochastic models such as the satellite elevation angle model and SNR-based models (SIGMA-∊ model and our modified SNR-based model), and our own novel ray-tracing method. The techniques are tested with both real and simulated data, the real test datasets have been collected on the Laboratoire Central des Ponts et Chaussées (LCPC) testbed near Nantes in France, and on the campus of the University of Nottingham during SPACE data collection experiments.

This paper proposes a numerical algorithm designed to integrate the GPS satellite perturbed orbit. The numerical solution is applied to integrate the differential equation of perturbed motion that frames the significant perturbing accelerations. Perturbing potentials are given and the corresponding accelerations in Cartesian coordinates are subsequently deduced. The C++ program that implements a fourth-order Runge-Kutta algorithm is described and comment is made on the perturbed orbit integration results. The paper offers a set of conclusions that will hopefully create a quantitative and qualitative image of GPS orbital perturbations and open a few ways ahead.

Indoor positioning imposes demanding requirements on the design of Global Navigation Satellite System (GNSS) sensors for both the acquisition and tracking functions. Although different combinations of coherent and non-coherent integration periods of a GNSS signal can be used to achieve reliable acquisition of the GNSS signals and indoors positioning, there are limitations to the extent that the integration period of the signal energy can be increased set by the receiver and satellite dynamics and the stability of the local oscillator. Assisting networks for GNSS applications (AGNSS) provide users with the capability of using long integration periods, enabling them to acquire indoor signals at low Carrier to Noise Ratio (CNR) values, where CNR is defined as the ratio of the received signal power over the noise density in units of dB-Hz. In this work we propose and evaluate the potential of a new method that will provide the user with an additional signal energy margin for accurate and reliable indoor positioning, with or without relying on assisted GNSS-type algorithms. The technique proposed here is based on the coherent and non-coherent combination of the energy of signals transmitted from the same GNSS satellite on different frequencies using the multiple open service signals that are to be provided by the Galileo system and under the GPS modernisation. This paper shows the improvement to the receiver acquisition and tracking performance using the proposed technique of combining energies at the L1, L2 and L5 bands for both data and pilot signals.

The central task of GPS/INS integration is to effectively blend GPS and INS data together to generate an optimal solution. The present data fusion algorithms, which are mostly based on Kalman filtering (KF), have several limitations. One of those limitations is the stringent requirement on precise a priori knowledge of the system models and noise properties. Uncertainty in the covariance parameters of the process noise (Q) and the observation errors (R) may significantly degrade the filtering performance. The conventional way of determining Q and R relies on intensive analysis of empirical data. However, the noise levels may change in different applications. Over the past few decades adaptive KF algorithms have been intensively investigated with a view to reducing the influence of the Q and R definition errors. The covariance matching method has been shown to be one of the most promising techniques. This paper first investigates the utilization of an online stochastic modelling algorithm with regards to its parameter estimation stability, convergence, optimal window size, and the interaction between Q and R estimations. Then a new adaptive process noise scaling algorithm is proposed. Without artificial or empirical parameters being used, the proposed adaptive mechanism has demonstrated the capability of autonomously tuning the process noise covariance to the optimal magnitude, and hence improving the overall filtering performance.