Washington Ochieng

AN EXTENDED KALMAN FILTER ALGORITHM FOR INTEGRATING GPS AND LOW COST DEAD RECKONING SYSTEM DATA FOR VEHICLE PERFORMANCE AND EMISSIONS MONITORING

This paper describes the features of an extended Kalman filter algorithm designed to support the navigational function of a real-time vehicle performance and emissions monitoring system currently under development. The Kalman filter is used to process global positioning system (GPS) data enhanced with dead reckoning (DR) in an integrated mode, to provide continuous positioning in built-up areas. The dynamic model and filter algorithms are discussed in detail, followed by the findings based on computer simulations and a limited field trial carried out in the Greater London area. The results demonstrate that use of the extended Kalman filter algorithm enables the integrated system employing GPS and low cost DR devices to meet the required navigation performance of the device under development.

Factors Affecting Air Traffic Controller Workload: Multivariate Analysis Based on Simulation Modeling of Controller Workload

Airspace capacity in a high-density air traffic network is determined by controller workload. Controller workload is primarily affected by the features of the air traffic and air traffic control (ATC) sector. Factors that affect controller workload are examined by, first, a review of the literature on this subject and then a multivariate analysis of the data obtained from simulations of a model of air traffic controller workload. This model, the European Airspace Model (EAM), has been widely used in European airspace planning. The results from simulations of five very different areas of European airspace are analyzed. In particular, the results of principal components analysis and factor analysis provide a valuable insight into the aircraft profile factors affecting controller workload.

URBAN ROAD TRANSPORT NAVIGATION: PERFORMANCE OF THE GLOBAL POSITIONING SYSTEM AFTER SELECTIVE AVAILABILITY

Satellite navigation systems have a potential to support multi-modal transport navigation requirements. In road transport, the global positioning system (GPS) is currently supporting a wide variety of in-car navigation and transport telematics systems. The performance of GPS has in the past been limited by the artificial degradation of the signal through the process of selective availability (SA). With SA operational, the instantaneous horizontal positional accuracy was 100 m 95% of the time. Additional infrastructure was used with the differential concept (where range errors are determined at a known location and transmitted to users) to improve this to the level of a few metres. The US Government on 1 May 2000 removed SA. This paper presents the results of a study to assess and characterise the post-SA performance of GPS for positioning vehicles in urban areas. This is an important functionality of advanced transport telematics systems that aim to address everyday problems associated with road transport, particularly in urban areas. The performance assessment addresses, in varying levels of detail, the issues of service coverage, positioning accuracy, integrity and availability of service. Comparison is made with the results of a previous study conducted when SA was turned on. The results show an improvement in stand-alone navigation accuracy without SA compared to the period when SA was operational. Furthermore, no significant difference is seen between the level of accuracy achievable with differential positioning and post-SA stand-alone navigation. The parameters that characterise the performance of GPS determined at the analysis stage have been used to specify an architecture for a local navigation system for urban areas.

Failure Modes and Models for Integrated GPS/INS Systems

GPS is the most widely used global navigation satellite system. By design, there is no provision for real time integrity information within the Standard Positioning Service (SPS). However, in safety critical sectors like aviation, stringent integrity performance requirements must be met. This can be achieved externally or at the receiver level through receiver autonomous integrity monitoring (RAIM). The latter is a cost effective method that relies on data consistency, and therefore requires redundant measurements. An external aid to provide this redundancy can be in the form of an Inertial Navigation System (INS). This should enable continued performance even during RAIM holes (when no redundant satellite measurements are available). However, due to the inclusion of an additional system and the coupling mechanism, integrity issues become more challenging. To develop an effective integrity monitoring capability, a good understanding of the potential failure modes of the integrated system is vital. In this paper potential failure modes of integrated GPS/INS systems are identified. This is followed by the specification of corresponding models that would be required to investigate the capability of existing integrity algorithms and to develop enhancements or new algorithms.

Enhanced Precise Point Positioning for GNSS Users

This paper summarizes the main results obtained during the development of an Enhanced Precise Point Positioning (EPPP) Global Navigation Satellite Systems multifrequency user algorithm. The main innovations include the application of precise ionospheric corrections to facilitate the resolution of undifferenced carrier phase ambiguities, ambiguity validation, and integrity monitoring. The performance of the EPPP algorithm in terms of accuracy, convergence time, and integrity is demonstrated with actual GPS and simulated Galileo data. This can be achieved with very limited bandwidth requirements for EPPP users (less than 300 b/s for dual-frequency GPS data).

Validation of map matching algorithms using high precision positioning with GPS

Map Matching (MM) algorithms are usually employed for a range of transport telematics applications to correctly identify the physical location of a vehicle travelling on a road network. Two essential components for MM algorithms are (1) navigation sensors such as the Global Positioning System (GPS) and dead reckoning (DR), among others, to estimate the position of the vehicle, and (2) a digital base map for spatial referencing of the vehicle location. Previous research by the authors (Quddus et al., 2003; Ochieng et al., 2003) has developed improved MM algorithms that take account of the vehicle speed and the error sources associated with the navigation sensors and the digital map data previously ignored in conventional MM approaches. However, no validation study assessing the performance of MM algorithms has been presented in the literature. This paper describes a generic validation strategy and results for the MM algorithm previously developed in Ochieng et al. (2003). The validation technique is based on a higher accuracy reference (truth) of the vehicle trajectory as determined by high precision positioning achieved by the carrier-phase observable from GPS. The results show that the vehicle positions determined from the MM results are within 6 m of the true positions. The results also demonstrate the importance of the quality of the digital map data to the map matching process.

Estimation of European Airspace Capacity from a Model of Controller Workload

This paper deals with the modelling of airspace capacity in Europe by first considering the factors that affect controller workload and then using a model, aided by the appropriate analytical techniques, to make an estimate of airspace capacity. The results show that capacity can be estimated based on the combination of different types of air traffic movement in a sector. The model has been used to provide airspace capacity estimates and utilisation measures for ATC sectors in Europe.

An Assessment of the RAIM Performance of a Combined Galileo/GPS Navigation System Using the Marginally Detectable Errors (MDE) Algorithm

Integrity relates to the trust that can be placed in the correctness of information supplied by a navigation system. It includes the ability of the navigation system to provide timely warning to users when the system fails to meet its stated accuracy. Specifically, a navigation system is required to deliver a warning (alarm) when the error in the derived user position solution exceeds an allowable level (alarm limit). This warning must be issued to the user within a given period of time (time-to-alarm) and with a given probability (integrity risk). The two main approaches to monitoring the integrity of satellite navigation systems are Receiver Autonomous Integrity Monitoring (RAIM), and monitoring based on an independent network of integrity monitoring stations and a dedicated Ground Integrity Channel (GIC). More recently Satellite Autonomous Integrity Monitoring (SAIM) methods have also been investigated.This article presents the results of a study to assess the RAIM capability of the Galileo system when used alone and when combined with the Global Positioning System (GPS). The assessment was based on the Marginally Detectable Error (MDE) algorithm. The results show a significant improvement in the capability to perform RAIM using a combined Galileo/GPS system compared to the performance using the Galileo system alone. This study was supported by Alcatel Space and was a contribution to the Galileo definition studies carried out for the European Community under the GALA project.

Performance Evaluation of a Novel 4D Trajectory Prediction Model for Civil Aircraft

Future air traffic management will require a variety of automated decision support tools to provide conflict-free trajectories and their associated error margins. The ability to correctly forecast aircraft trajectories, i.e. trajectory prediction, is the central component of such automated tools, which will enable continued provision of safe and efficient services in increasingly congested skies. Current approaches for trajectory prediction, available in the open literature, make a number of assumptions in order to simplify the mathematical models of aircraft motion. Furthermore, many existing methods perform three-dimensional trajectory prediction, in which information on expected times of arrival at significant points along the intended aircraft route is not considered. This results in inaccurate trajectories not suitable for conflict detection and resolution. This paper presents a novel four-dimensional trajectory prediction scheme that makes full use of data on expected times of arrival. A three dimensional point-mass model for a standard civil aircraft is used to emulate aircraft dynamics, while the aircraft operating mode is characterised through a set of discrete variables. The aircraft performance model used relies on the EUROCONTROL Base of Aircraft Data (BADA) set and the computed trajectory accounts for the effects of wind. Inputs include navigation data and aircraft intent information, which unambiguously define the trajectory to be computed according to the flight plan. In the proposed model, aircraft intent information is summarised in a simple, but effective, set of instructions contained in a Flight Script. Furthermore, two key innovations to trajectory prediction are introduced. Firstly, a novel scheme to emulate the control system used for aircraft lateral guidance is proposed and secondly, on the basis of aircraft intent information, a new procedure to estimate speed is presented. The performance of the enhanced trajectory model proposed is quantified using a detailed operational dataset (real flight data) captured in a European airspace. The results show that, over an extended time-horizon, the enhanced model is more accurate than two representative existing methods, and that it is suitable for reliable trajectory prediction.

On the Effect of Localization Errors on Geographic Routing in Sensor Networks

Recently, network localization systems that are based on inter-node ranges have received significant attention. Geographic routing has been considered an application which can utilize the location information from these localization systems. In this paper, we firstly recognize that sensor network localization algorithms generate positioning data with different error patterns compared to those networks where node positions are determined directly from GNSS measurements. Secondly, by simulating practical sensor network scenarios using data from our localization algorithm, we observe that existing geographic routing algorithms in wireless sensor networks (WSNs) adopt very simplistic methods in the treatment of position error, without due consideration of error distribution. Additionally, an insight is given into localization algorithms for WSNs with inhomogeneous error environments. Our observations represent an initial step toward a detailed understanding and design of efficient geographic routing algorithms in location aware WSNs.