Versions of this paper were first presented at the Royal Institute of Navigation GNSS Vulnerabilities and Solutions Conference held at Baska, Croatia in September 2008 and the Royal Institute of Navigation NAV 08 Conference held at Church House, Westminster, London in October 2008.

The US Global Positioning System (GPS) is currently the primary source of Position, Navigation and Timing (PNT) information in maritime applications, whether stand-alone or augmented with additional systems. This situation will continue in the future with GPS, possibly together with other Global Navigation Satellite Systems (GNSS) e.g. Galileo, being the core PNT technology for e-Navigation – the future digital maritime architecture. GPS signals, measured at the surface on the Earth, are very weak. As such, the system is vulnerable to unintentional interference and jamming, resulting in possible denial of service over large geographical areas. The result of such interference could be the complete failure of the mariner's GPS receiver or, possibly worse, the presentation to the mariner of hazardously misleading information (HMI) for navigation and situational awareness, depending on how the GPS receiver reacts to the jamming incident. Recognising this, the General Lighthouse Authorities of the United Kingdom and Ireland (GLA), in collaboration with the UK Ministry of Defence (MOD) Defence Science and Technology Laboratory (DSTL), have conducted a series of sea-trials with the aim of identifying the full effects of GPS jamming on safe navigation at sea.

This paper presents the key findings of these trials and provides important information on the effect of GPS denial. The GLA are playing a pivotal role in the establishment of eLoran as an independent source of PNT, taking advantage of eLoran's complementary nature, having dissimilar failure modes to GPS and the future GNSS. This paper provides information on the performance of an eLoran receiver in an area of GPS service denial. The paper presents the rationale for the work, details the system architecture employed, the data gathering efforts and finally the data analysis procedures, results and conclusions.

A version of this paper was first presented at the Royal Institute of Navigation NAV 08 Conference held at Church House, Westminster, London in October 2008.

The North Sea oil platforms are reliant on regular and reliable helicopter operations for the movement of staff and supplies. The environment is challenging and there have been six fatal accidents incurring the loss of 79 lives since the mid-1970s. The need for accurate and reliable helicopter approach procedures has been identified and this paper reports the results of a feasibility study into the use of EGNOS-based approaches to oil platforms in the North Sea.

A version of this paper was first presented at the Royal Institute of Navigation NAV 08 Conference held at Church House, Westminster, London in October 2008.

SESAR is Europe's ‘Single European Sky Air traffic Research system’, targeted at post-2020. The vision is to integrate and implement new technologies to improve air traffic management (ATM) performance. The focus for planning and executing system operations will increasingly be aircraft navigating high-quality 4D trajectories: a 4D trajectory is the aircraft path, three space dimensions plus time, from gate-to-gate, i.e. including the path along the ground at the airport. A 20+year ATM plan has to use limited information on the success of innovations and the development of large-scale, often safety critical, software, which by its nature can take markedly longer and cost markedly more than early estimates. SESAR must be sufficiently flexible in deployment to maximise financial benefits to individual stakeholders using their specific financial criteria. Airline needs are the main ATM system/business drivers. Airlines do not want to commit to developing an ‘ultra-modern system’ per se, but rather to one that makes business-sensible investments in new technologies that are indispensable for achieving improved safety and meeting projected capacity requirements. The approach has been to use simple corporate finance ideas to examine the different viewpoints and business environments of air traffic service suppliers (ANSPs) and individual airlines. The key decision-making point is that ANSPs act as an agent for airlines as a whole. The key financial point is that a typical airline has to work hard to survive and needs quick paybacks on investment. The design of the SESAR R&D and project portfolios can learn lessons from information technology systems design and deployment. ‘Real option analysis’ of systems can increase business value by improving the sequencing and partitioning of projects, helping to ensure that the system is adaptable to technological innovation and changes in business needs.

A version of this paper was first presented at the Royal Institute of Navigation NAV 08 Conference held at Church House, Westminster, London in October 2008.

There exist various applications for indoor positioning, amongst which indoor positioning and tracking in urban environments has gained significant attention. Some user communities, like fire fighters, ideally require indoor accuracy of less than one metre, with accuracies of less than six metres acceptable by some other user communities. Achieving this level of accuracy requires a detailed profiling of error sources so that they can be better understood so that, in turn, indoor positioning accuracy in the presence of these errors can be further improved. Some well known error sources like multipath, NLOS (non line of sight), oscillator drift, dilution of precision and others have been studied and can be found in the literature. A less well known error source that can substantially affect indoor positioning accuracy are the effects of the dielectric properties of building materials on propagation delay.

Various RF and non-RF based prototypes that claim to be suitable for indoor positioning can be found in the literature. Most of the existing literature discusses algorithms and summarizes the positioning results that were achieved during field tests using a prototype system or, more commonly, simulations. Little of this existing literature provides a breakdown of the total navigation system errors observed with the objective of analyzing the contribution of each error source independently.

The paper will first provide a brief overview of the precision personnel locator system developed at the Worcester Polytechnic Institute. The field tests and observed indoor positioning results using this RF prototype will then be summarized and used to provide a baseline to establish a system error budget. The total observed error will be broken down and a detailed analysis of each of the error sources will be presented based on actual measured data in a variety of indoor environments. This leads to a better understanding of how each error source affects indoor positioning accuracy. Each of the error sources can then be independently optimized to minimize the observed errors. Specifically, the interplay between the dielectric properties and multipath profiles will be highlighted. This paper will conclude by presenting an error budget which can be used as a practical lower bound when designing precise indoor positioning systems.

Global Navigation Satellite System (GNSS) Receiver Autonomous Integrity Monitoring (RAIM) is essential for safety-of-life and liability critical applications. This paper discusses two fundamentally different ways to assess the integrity risk of an operation with RAIM, based on a different amount of information available: the expected (or average) performance that is computed using the GNSS models only and the real-time (or actual) performance, which also uses information on the internal status of a GNSS receiver. It is shown both theoretically and by simulation that the real-time integrity risk significantly exceeds the expected risk after the detection and exclusion of a failing satellite. Therefore, while most published RAIM algorithms base their performance assessment on the expected performance only, this is only correct when the requirements allow the risk evaluation to be averaged over multiple operations. However, when the GNSS integrity requirement is to be applied on a ‘per operation’ basis, real-time integrity measures are more appropriate.

For high-precision real-time kinematics (RTK) and safety-of-life Global Navigation Satellite Systems (GNSS), it is critical to track the carrier reliably without interruptions. We develop hardware-oriented robust on-line cycle slip and loss detection logic for a single-frequency stand-alone aviation receiver. The moving average statistics of time-differenced frequency-lock loop (FLL) are shown to provide a robust and fixed detection threshold for cycle loss detection. A Monte-Carlo simulation shows that the detection performance remains robust when aviation dynamics from minimum operational performance standard (MOPS) are added to a simulated strong scintillation.

This paper builds on prior research into the application of particle swarm optimisation to autonomous vehicle control in search roles. It examines the use of naturally inspired search strategies to enhance the performance of groups of sensor-based vehicles in applications where there is no knowledge a priori regarding target presence, location, distribution or behaviour (movement). This paper first briefly reviews existing ethological research into search strategies in the natural world, identifying three types of random walk, two multi-phase strategies and two species-specific strategies for further investigation. Experiments are then performed within a simulation environment to compare the performance of naturally inspired strategies with deterministic patterns and random movement, when searching for both static and dynamic targets. Results indicate that performance improvements can be realised, provided that critical relationships within the application domain broadly match those existing in the underlying natural metaphor.

A navigation integration processing scheme, called the strong tracking unscented Kalman filter (STUKF), is based on the combination of an unscented Kalman filter (UKF) and a strong tracking filter (STF). The UKF employs a set of sigma points by deterministic sampling, such that the linearization process is not necessary, and therefore the error caused by linearization as in the traditional extended Kalman filter (EKF) can be avoided. As a type of adaptive filter, the STF is essentially a nonlinear smoother algorithm that employs suboptimal multiple fading factors, in which the softening factors are involved. In order to resolve the shortcoming in traditional approach for selecting the softening factor through personal experience or computer simulation, a novel scheme called the fuzzy strong tracking unscented Kalman filter (FSTUKF) is presented where the Fuzzy Logic Adaptive System (FLAS) is incorporated for determining the softening factor. The proposed FSTUKF algorithm shows promising results in estimation accuracy when applied to the integrated navigation system design, as compared to the EKF, UKF and STUKF approaches.

In the work package ‘Integrated Positioning’ of the Ubiquitous Cartography for Pedestrian Navigation project (UCPNAVI) alternative location methods using active Radio Frequency Identification (RFID) are investigated for positioning of pedestrians in areas where no GNSS position determination is possible due to obstruction of the satellite signals. In most common RFID applications, positioning is performed using cell-based positioning. RFID tags can be installed at active landmarks (i.e., known locations) in the surroundings and a user equipped with an RFID reader can be positioned using Cell of Origin (CoO). The positioning accuracy, however, depends on the size of the cell defined by the maximum range of the signal. Using long range RFID for positioning the cell size can be quite large, i.e., around 20 m. Therefore, the paper proposes two new methods for positioning, i.e., trilateration and location fingerprinting based on received signal strength indication (RSSI) if more than one RFID tag is visible. The trilateration approach is based on the deduction of ranges to the RFID tags from RSSI. An iterative approach to model the signal propagation will be introduced, i.e., the International Telecommunication Union (ITU) indoor location model that can be simplified to a logarithmic model, and a simple polynomial model is employed for the signal strength to range conversion. In a second attempt, location fingerprinting based on RSSI is investigated. In this case, RSSI is measured in a training phase at known locations inside the building and stored in a database. In the positioning phase these measurements are used together with the current measurements to obtain the current location of the user. For the estimation of the current location different approaches are employed and tested, i.e., a direction-based approach, a tag-based approach, a direction-tag-based approach and a heading-based approach. Using trilateration or fingerprinting positioning accuracies on the one to a few metres level can usually be achieved. The concept and the iterative approach of the different methods and test results are discussed in this paper.

The troposphere affects electromagnetic signal propagation causing signal path bending and the alteration of the electromagnetic wave velocity. Tropospheric delay can introduce a considerable error in satellite positioning if it is not properly estimated. The GPS signal delay can vary from 2 to 20 m depending on the elevation angles between the receiver and the satellite. Two basic types of delay prediction models exist. The first use surface meteorological parameters to estimate the value of the tropospheric delay, and the other models that do not require real-time meteorological input use average and seasonal variation data related to the receiver's latitude and day-of-year. This paper compares the performance of both types of model over a period of one year, comprising all seasons, to verify their accuracy over a longer period. The Saastamoinen model, known as one of the best performing prediction models, was taken as a reference and the global EGNOS model was used to check how the global estimates of the yearly averages of the meteorological parameters and their related seasonal variations comply with the real-time surface parameters.

The accurate location of a vehicle in the road is one of the most important challenges in the automotive field. The need for accurate positioning affects several in-vehicle systems like navigators, lane departure warning systems, collision warning and other related sectors such as digital cartography suppliers. The aim of this paper is to evaluate high precision positioning systems that are able to supply an on-the-centimetre accuracy source to develop on-the-lane positioning systems and to be used in future applications as an information source for autonomous vehicles that circulate at high speeds on public roads. In this paper we have performed some on-road experiments, testing several GPS-based systems: Autonomous GPS; RTK Differential GPS with a proprietary GPS base station; RTK Differential GPS connected to the public GPS base station network of the National Geographic Institute of Spain via vehicle-to-infrastructure GPRS communications; and GPS combination with inertial measurement systems (INS) for position accuracy maintenance in degraded satellite signal reception areas. In these tests we show the validity and the comparison of these positioning systems, allowing us to navigate, in some cases, on public roads at speeds near 120 km/h and up to 100 km from the start position without any significant accuracy reduction.