The International GNSS Service (IGS) is an international activity involving more than 200 participating organisations in over 80 countries with a track record of one and a half decades of successful operations. The IGS is a service of the International Association of Geodesy (IAG). It primarily supports scientific research based on highly precise and accurate Earth observations using the technologies of Global Navigation Satellite Systems (GNSS), primarily the US Global Positioning System (GPS). The mission of the IGS is "to provide the highest-quality GNSS data and products in support of the terrestrial reference frame, Earth rotation, Earth observation and research, positioning, navigation and timing and other applications that benefit society". The IGS will continue to support the IAG's initiative to coordinate cross-technique global geodesy for the next decade, via the development of the Global Geodetic Observing System (GGOS), which focuses on the needs of global geodesy at the mm-level. IGS activities are fundamental to scientific disciplines related to climate, weather, sea level change, and space weather. The IGS also supports many other applications, including precise navigation, machine automation, and surveying and mapping. This article discusses the IGS Strategic Plan and future directions of the globally-coordinated ∼400 station IGS network, tracking data and information products, and outlines the scope of a few of its numerous

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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.

Location fingerprinting in wireless LAN (WLAN) positioning has received much attention recently. One of the key issues of this technique is generating the database of 'fingerprints'. The conventional method does not utilise the spatial correlation of measurements sampled at adjacent reference points (RPs), and the 'training' process is not an easy task. A new method based on kriging is presented in this paper. An experiment shows that the new method can not only achieve more accurate estimation, but can also greatly reduce the workload and save training time. This can make the fingerprinting technique more flexible and easier to implement.

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This Editorial lead article for the Journal of Location Based Services surveys this complex and multi-disciplinary field and identifies the key research issues. Although this field has produced early commercial disappointments, the inevitability that pervasive location-aware services on mobile devices will emerge means that much research is needed to inform these developments. The article reviews firstly: the science and technology of positioning, geographic information science, mobile cartography, spatial cognition and interfaces, information science, ubiquitous computing; and secondly the business, content and legal, social and ethics aspects, before synthesising the key issues for this new field.

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