21 resultados para Taxi GPS data

em BORIS: Bern Open Repository and Information System - Berna - Suiça


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A joint reprocessing of GPS, GLONASS and SLR observations has been carried out at TU Dresden, TU Munich, AIUB and ETH Zurich. Common a priori models have been applied for the processing of all types of observation to ensure both consistent parameter estimates and the rigorous combination of microwave and optical measurements. Based on that reprocessing results, we evaluate the impact of adding GLONASS observations to the standard GPS data processing. In particular, changes in station position time series and day boundary overlaps of consecutive satellite arcs are analyzed. In addition, the GNSS orbits derived from microwave measurements are validated using independent SLR range measurements. Our SLR residuals indicate a significant improvement compared to previous results. Furthermore, we evaluate the performance of our high-rate (30s) combined GNSS satellite clocks and discuss associated zero-difference phase residuals.

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The accuracy of Global Positioning System (GPS) time series is degraded by the presence of offsets. To assess the effectiveness of methods that detect and remove these offsets, we designed and managed the Detection of Offsets in GPS Experiment. We simulated time series that mimicked realistic GPS data consisting of a velocity component, offsets, white and flicker noises (1/f spectrum noises) composed in an additive model. The data set was made available to the GPS analysis community without revealing the offsets, and several groups conducted blind tests with a range of detection approaches. The results show that, at present, manual methods (where offsets are hand picked) almost always give better results than automated or semi‒automated methods (two automated methods give quite similar velocity bias as the best manual solutions). For instance, the fifth percentile range (5% to 95%) in velocity bias for automated approaches is equal to 4.2 mm/year (most commonly ±0.4 mm/yr from the truth), whereas it is equal to 1.8 mm/yr for the manual solutions (most commonly 0.2 mm/yr from the truth). The magnitude of offsets detectable by manual solutions is smaller than for automated solutions, with the smallest detectable offset for the best manual and automatic solutions equal to 5 mm and 8 mm, respectively. Assuming the simulated time series noise levels are representative of real GPS time series, robust geophysical interpretation of individual site velocities lower than 0.2–0.4 mm/yr is therefore certainly not robust, although a limit of nearer 1 mm/yr would be a more conservative choice. Further work to improve offset detection in GPS coordinates time series is required before we can routinely interpret sub‒mm/yr velocities for single GPS stations.

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The GOCE satellite was orbiting the Earth in a Sun-synchronous orbit at a very low altitude for more than 4 years. This low orbit and the availability of high-quality data make it worthwhile to assess the contribution of GOCE GPS data to the recovery of both the static and time-variable gravity fields. We use the kinematic positions of the official GOCE precise science orbit (PSO) product to perform gravity field determination using the Celestial Mechanics Approach. The generated gravity field solutions reveal severe systematic errors centered along the geomagnetic equator. Their size is significantly coupled with the ionospheric density and thus generally increasing over the mission period. The systematic errors may be traced back to the kinematic positions of the PSO product and eventually to the ionosphere-free GPS carrier phase observations used for orbit determination. As they cannot be explained by the current higher order ionospheric correction model recommended by the IERS Conventions 2010, an empirical approach is presented by discarding GPS data affected by large ionospheric changes. Such a measure yields a strong reduction of the systematic errors along the geomagnetic equator in the gravity field recovery, and only marginally reduces the set of useable kinematic positions by at maximum 6 % for severe ionosphere conditions. Eventually it is shown that GOCE gravity field solutions based on kinematic positions have a limited sensitivity to the largest annual signal related to land hydrology.

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Navigation of deep space probes is most commonly operated using the spacecraft Doppler tracking technique. Orbital parameters are determined from a series of repeated measurements of the frequency shift of a microwave carrier over a given integration time. Currently, both ESA and NASA operate antennas at several sites around the world to ensure the tracking of deep space probes. Just a small number of software packages are nowadays used to process Doppler observations. The Astronomical Institute of the University of Bern (AIUB) has recently started the development of Doppler data processing capabilities within the Bernese GNSS Software. This software has been extensively used for Precise Orbit Determination of Earth orbiting satellites using GPS data collected by on-board receivers and for subsequent determination of the Earth gravity field. In this paper, we present the currently achieved status of the Doppler data modeling and orbit determination capabilities in the Bernese GNSS Software using GRAIL data. In particular we will focus on the implemented orbit determination procedure used for the combined analysis of Doppler and intersatellite Ka-band data. We show that even at this earlier stage of the development we can achieve an accuracy of few mHz on two-way S-band Doppler observation and of 2 µm/s on KBRR data from the GRAIL primary mission phase.

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The Gravity field and steady-state Ocean Circulation Explorer (GOCE) was the first Earth explorer core mission of the European Space Agency. It was launched on March 17, 2009 into a Sun-synchronous dusk-dawn orbit and re-entered into the Earth’s atmosphere on November 11, 2013. The satellite altitude was between 255 and 225 km for the measurement phases. The European GOCE Gravity consortium is responsible for the Level 1b to Level 2 data processing in the frame of the GOCE High-level processing facility (HPF). The Precise Science Orbit (PSO) is one Level 2 product, which was produced under the responsibility of the Astronomical Institute of the University of Bern within the HPF. This PSO product has been continuously delivered during the entire mission. Regular checks guaranteed a high consistency and quality of the orbits. A correlation between solar activity, GPS data availability and quality of the orbits was found. The accuracy of the kinematic orbit primarily suffers from this. Improvements in modeling the range corrections at the retro-reflector array for the SLR measurements were made and implemented in the independent SLR validation for the GOCE PSO products. The satellite laser ranging (SLR) validation finally states an orbit accuracy of 2.42 cm for the kinematic and 1.84 cm for the reduced-dynamic orbits over the entire mission. The common-mode accelerations from the GOCE gradiometer were not used for the official PSO product, but in addition to the operational HPF work a study was performed to investigate to which extent common-mode accelerations improve the reduced-dynamic orbit determination results. The accelerometer data may be used to derive realistic constraints for the empirical accelerations estimated for the reduced-dynamic orbit determination, which already improves the orbit quality. On top of that the accelerometer data may further improve the orbit quality if realistic constraints and state-of-the-art background models such as gravity field and ocean tide models are used for the reduced-dynamic orbit determination.

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The Gravity field and steady-state Ocean Circulation Explorer (GOCE) is now in orbit for more than four years. This is longer than the originally planned lifetime of the satellite and after three years on the same altitude the satellite has been lowered to 235 km in several steps. In the frame of the GOCE High-level Processing Facility the Astronomical Institute of the University of Bern (AIUB) is responsible for the determination of the official Precise Science Orbit (PSO) product. Kinematic GOCE orbits are part of this product and are used by several institutions in- and outside the HPF for determining the low degrees of the Earth’s gravity field. AIUB GOCE GPS-only gravity field solutions using the Celestial Mechanics Approach and covering the Release 4 period as well as a more recent time interval at the lower orbit altitude are shown and discussed. Special attention is paid to the impact of systematic deficiencies in the kinematic orbits on the resulting gravity fields, e.g., related to the geomagnetic equator, and on possibilities to get rid of them.

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An ever increasing number of low Earth orbiting (LEO) satellites is, or will be, equipped with retro-reflectors for Satellite Laser Ranging (SLR) and on-board receivers to collect observations from Global Navigation Satellite Systems (GNSS) such as the Global Positioning Sys- tem (GPS) and the Russian GLONASS and the European Galileo systems in the future. At the Astronomical Insti- tute of the University of Bern (AIUB) LEO precise or- bit determination (POD) using either GPS or SLR data is performed for a wide range of applications for satellites at different altitudes. For this purpose the classical numeri- cal integration techniques, as also used for dynamic orbit determination of satellites at high altitudes, are extended by pseudo-stochastic orbit modeling techniques to effi- ciently cope with potential force model deficiencies for satellites at low altitudes. Accuracies of better than 2 cm may be achieved by pseudo-stochastic orbit modeling for satellites at very low altitudes such as for the GPS-based POD of the Gravity field and steady-state Ocean Circula- tion Explorer (GOCE).

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BACKGROUND: Pain is a common experience in later life. There is conflicting evidence of the prevalence, impact, and context of pain in older people. GPs are criticised for underestimating and under-treating pain. AIM: To assess the extent to which older people experience pain, and to explore relationships between self-reported pain and functional ability and depression. DESIGN OF STUDY: Secondary analysis of baseline data from a randomised controlled trial of health risk appraisal. SETTING: A total of 1090 community-dwelling non-disabled people aged 65 years and over were included in the study from three group practices in suburban London. METHOD: Main outcome measures were pain in the last 4 weeks and the impact of pain, measured using the 24-item Geriatric Pain Measure; depression symptoms captured using the 5-item Mental Health Inventory; social relationships measured using the 6-item Lubben Social Network Scale; Basic and Instrumental Activities of Daily Living and self-reported symptoms. RESULTS: Forty-five per cent of women and 34% of men reported pain in the previous 4 weeks. Pain experience appeared to be less in the 'oldest old': 27.5% of those aged 85 years and over reported pain compared with 38-53% of the 'younger old'. Those with arthritis were four times more likely to report pain. Pain had a profound impact on activities of daily living, but most of those reporting pain described their health as good or excellent. Although there was a significant association between the experience of pain and depressed mood, the majority of those reporting pain did not have depressed mood. CONCLUSION: A multidimensional approach to assessing pain is appropriate. Primary care practitioners should also assess the impact of pain on activities of daily living.

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BACKGROUND Muscle strength greatly influences gait kinematics. The question was whether this association is similar in different diseases. METHODS Data from instrumented gait analysis of 716 patients were retrospectively assessed. The effect of muscle strength on gait deviations, namely the gait profile score (GPS) was evaluated by means of generalised least square models. This was executed for seven different patient groups. The groups were formed according to the type of disease: orthopaedic/neurologic, uni-/bilateral affection, and flaccid/spastic muscles. RESULTS Muscle strength had a negative effect on GPS values, which did not significantly differ amongst the different patient groups. However, an offset of the GPS regression line was found, which was mostly dependent on the basic disease. Surprisingly, spastic patients, who have reduced strength and additionally spasticity in clinical examination, and flaccid neurologic patients showed the same offset. Patients with additional lack of trunk control (Tetraplegia) showed the largest offset. CONCLUSION Gait kinematics grossly depend on muscle strength. This was seen in patients with very different pathologies. Nevertheless, optimal correction of biomechanics and muscle strength may still not lead to a normal gait, especially in that of neurologic patients. The basic disease itself has an additional effect on gait deviations expressed as a GPS-offset of the linear regression line.