Wavelet packets based denoising method for measurement domain repeat-time multipath filtering in GPS static high-precision positioning

Repeatable satellite orbits can be used for multipath mitigation in GPS-based deformation monitoring and other high-precision GPS applications that involve continuous observation with static antennas. Multipath signals at a static station repeat when the GPS constellation repeats given the same site environment. Repeat-time multipath filtering techniques need noise reduction methods to remove the white noise in carrier phase measurement residuals in order to retrieve the carrier phase multipath corrections for the next day. We propose a generic and robust three-level wavelet packets based denoising method for repeat-time-based carrier phase multipath filtering in relative positioning; the method does not need tuning to work with different data sets. The proposed denoising method is tested rigorously and compared with two other denoising methods. Three rooftop data sets collected at the University of Nottingham Ningbo China and two data sets collected at three Southern California Integrated GPS Network high-rate stations are used in the performance assessment. Test results of the wavelet packets denoising method are compared with the results of the resistor–capacitor (RC) low-pass filter and the single-level discrete wavelet transform (DWT) denoising method. Multipath mitigation efficiency in carrier phase measurement domain is shown by spectrum analysis of two selected satellites in two data sets. The positioning performance of the repeat-time-based multipath filtering techniques is assessed. The results show that the performance of the three noise reduction techniques is about 1–46 % improvement on positioning accuracy when compared with no multipath filtering. The statistical results show that the wavelet packets based denoising method is always better than the RC filter by 2–4 %, and better than the DWT method by 6–15 %. These results suggest that the proposed wavelet packets based denoising method is better than both the DWT method and the relatively simple RC low-pass filter for noise reduction in multipath filtering. However, the wavelet packets based denoising method is not significantly better than the RC filter

Assessment of Dynamic Geo-Positioning Using Multi-constellation GNSS in Challenging Environments

International audienceGlobal Navigation Satellite Systems (GNSS) provide accurate and reliable positioning solutions in open field environments. However, the positioning performance is not the same in dense urban areas, where satellite signals are blocked or reflected by tall buildings.A 3D city model, "Urban Trench", is introduced to simulate blockage and reflection of GNSS signals. The "Urban Trench" model assesses the reflection environment of the city and the non-light-of-sight (NLOS) ranging errors are corrected, based on satellite elevation and a 3D surface model. Subsequently, the metric of NLOS signal exclusion using an elevation-enhanced map is developed and tested using real vehicular data in the test urban network of Nantes. A GPS&GLONASS-constellation single-frequency receiver is used during the experiment. The performance of both systems, stand alone and in combination as dual-constellation, are presented, compared and evaluated, with and without "Urban Trench" model implementation. Additionally, a fault detection and exclusion test is applied, to check and enhance the integrity of the output

3-D localization of pavers in a Computer Integrated Road Construction context

International audienceThis paper presents a navigation system providing 3-D position and spatial attitude data for outdoor vehicles. Our system uses an odometer and an automatic laser theodolite, the data of which are fused using a Kalman filter. We show through different experiments carried out with the Sessyl test station that the high accuracies required for some civil-engineering tasks are fully satisfied, provided the beacons are properly positioned

Lane-level positioning for cooperative systems using EGNOS and enhanced digital maps

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How to Assess and Improve Satellite Positioning Performances in Urban Environments

International audienceSatellite positioning performances are critical for transport liability applications such as road user charging, or pay per use assurance. The scientific community has focused for several years on environments with favorable conditions (aviation, maritime, rural) and is now addressing transport applications including urban areas. This is the case of this paper that presents the result of a study co-financed by the National French Space Agency(CNES). This study aimed first to collect the positioning data in urban area of several GPS/EGNOS receivers (more than 1,5 millions of positions) in addition to their associated satellite raw data and the reference positions. Its goal was secondly to assess the performance using classical positioning algorithms and last to propose and assess improved algorithms.The authors present first how to obtain the true trajectory necessary for the performance assessments. The instrumentation they set-up on board a test vehicle is based on IXSEA LandINS inertial measurement unit hybridized with kinematics GPS and odometry. The reference trajectory obtained is analyzed, with the aim of qualifying its accuracy. Based on these measurements, the authors then present the performance improvements obtained using different techniques, in particular 2D techniques to improve availability in difficult area such as narrow streets, smoothing technique to optimize the filtering and local error modeling technique to assess in particular disturbing multipath effects.Thanks to the ground truth obtained in this benchmark, the authors demonstrate that these techniques bring a significant improvement to position data performances, enlarging that way the spectrum of liability-critical road transport applications in urban areas

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