Fig. 1 Simulated GPS three-frequency (red: L1, blue: L2, green: L5) multipath error in PRN02 in the LCPC dataset (relative permittivity =3.9) Phase multipath is one of the most crucial error sources in centimetre or millimetre level GNSS high precision positioning. Short-delay multipath is still especially difficult to detect or mitigate by the state-of-the-art hardwarebased techniques. Therefore, processing algorithm-based multipath mitigation methods are crucial for the further improvement of positioning accuracy, either integrated with other techniques or in a stand-alone mode. The effectiveness of some of these is, however, limited by the degrees of freedom in currently available solutions, i.e. insufficient satellites and signals. This problem is similar to the un-robustness and unreliability of some outlier detection techniques used in RAIM and other integrity algorithms in the current GPS system.

For the final evaluation of a GPS attitude determination algorithm (GADA), it was determined its true performance in terms of its accuracy, reliability and dynamic response. To accomplish that, a flight test campaign was carried out at the Brazilian Flight Test Division (GEEV) to validate the attitude determination algorithm. In this phase, the measured aircraft attitude was compared to a reference attitude, to allow the determination of the errors. The flight test campaign was carried out at the Brazilian’s Flight Test Division T-25C 1956 Basic Trainer aircraft manufactured by EMBRAER. The performance and accuracy of the system is demonstrated under static and dynamics tests profiles, which are fully compliant with the Federal Aviation Administration (FAA) Advisory Circular (AC) 25-7A. Dynamic response of the system is evaluated. Data reduction analysis of more than 12 hours flights showed that GADA errors are satisfactory for attitude determination. Also it is presented that its static accuracy is highly dependable of the Attitude Dilution of Precision (ADOP) while the dynamic accuracy depends upon the GPS receiver PLL model and coefficients

Satellite positioning is the term used to describe the determination of the absolute and relative coordinates of points on (or above) the Earth’s land or sea surface by processing measurements to, and/or form, artifi cial Earth Satellites. In this context, absolute coordinates refer to the position of a point in a specified coordinate system, whereas relative coordinates refer to the position of one point with respect to another (again in a specified coordinate system). Relative positions are generally more useful in surveying and can usually be more accurately determined.

GNSS positioning/navigation devices are rapidly merging into and changing our modern lives, just like the personal computer in the 1980’s and the cellular phone in the 1990’s. It is predicted that by 2012, the annual shipment of navigation devices will increase to over 65 million units, which is more than three times the 19.8 million shipped in 2006 [1]. Also in a situation personal computer and cellular phone ever faced, a higher standard service demand has been placed in front of the GNSS technology, and becoming a bottleneck before its potential mass market can be exploited.

SWEPOS™ is a network of GPS/GLONASS reference stations which began as a co-operation between the National Land Survey of Sweden and Onsala Space Observatory. The early design phases of SWEPOS were made in 1992. It was already then stated that the network should be of both scientific and practical benefit to the professional GNSS users and the public.

Contemporary positioning systems are usually composed of several navigation devices and an algorithm of joint data processing, which is often a Kalman filter [1, 8]. In aircraft positioning and navigation, INS/GNSS integrated systems are frequently applied [2, 3, 7]. Integration of INS and GNSS receiver via the Kalman filter presents one of the best achievements in positioning technology and one of the most successful applications of the Kalman filter. Although integration of INS and GNSS is very common, it is not the only possible option. Similar advantages can be gained in systems composed of INS and other than GNSS receiver radiotechnical devices.

Alternative location methods for absolute positioning in areas where no GNSS position determination is possible due to obstruction of the satellite signals are needed in mobile positioning. Active RFID (Radio Frequency Identification) can be used also for position determination, although the system was not only developed for positioning and tracking but mainly for identification of objects. Using RFID in positioning, different approaches can be distinguished, i.e., cell-based positioning if the RFID tags are installed at active landmarks (i.e., known locations) in the surroundings, trilateration if ranges to the RFID tags are deducted from received signal strength (RSS in RFID terms) values and location fingerprinting where the measured signal power levels are used directly to obtain a position fix. Using Cell of Origin (CoO) the achievable positioning accuracy depends on the size of the cell and is therefore usually several metres up to 10’s of metres using long range RFID equipment. Higher positioning accuracies can be obtained using trilateration and fingerprinting. In this paper the use of trilateration is investigated.

The ionosphere represents one of the most important error sources that affecting GPS positioning. It is strongly related to solar activity and geomagnetic ?eld. The GPS satellites and dual frequency receivers can be used to measure the Total Electron Content (TEC) of the Earth's ionosphere. Global electron content maps have been produced by various research centers using the world-wide permanent network of GPS receivers. In this study a rapid method of monitoring the ionospheric disturbance using dual frequency GPS data of the Aristotle University Thessaloniki (AUT1) permanent station is presented. The Total Electron Content can be determined using the so called Single Layer Model (SLM) of the ionosphere. The SLM is based on the assumption that all free electrons are concentrated in a spherical layer of in?nitesimal thickness (single layer) at height H above the earth's surface. The Total Electron Content is modeled as a truncated Taylor series with the geographical latitude and the hour angle of the sun as independent variables, using the L4 - geometry free linear combination. The results are con?rmed using global information for Sun spot and geomagnetic activity from NOAA and Kyoto University respectively.

In the last several years we have seen an explosion of consumer GPS products. Telematics systems, LBS applications on cell phones, GPS-enabled PDAs, and more novel GPS products such as pet finders have flooded the marketplace, with new products and applications announced almost daily. Likewise, public awareness of the potential utility of GPS has increased. Microsoft’s and Google’s entrance into the GPS and mapping market have helped accelerate consumer understanding and adoption of location technology. This is also causing a major demand among users of LBS technology to “show what is around me.” In a word, GPS is a general term in the marketplace to which consumers are accustomed in how they understand and explain all location-enabled products and applications. What’s interesting is that GPS is not even the positioning-enabling (or location-enabling) technology inside many of these new locationaware applications that are getting a lot of traction these days. Moreover, Google and the other online mapping consumer websites are a disruptive technology for GPS because they don’t require the use of GPS – users can either self provision by entering a street intersection or applications like Google Local and Microsoft Local Live use WiFi for location sensing to the nearest access point.

According to Skaloud [1999], the inertial sensor errors are composed of long term errors (low frequency components) and short term errors (high frequency components). Therefore, a conceptual plot of the frequency spectrum of the inertial sensor errors in the measurements can be illustrated as in Figure (1).