Current Issue : July - September Volume : 2015 Issue Number : 3 Articles : 5 Articles
The European GNSS, Galileo, is currently in its\nin-orbit validation (IOV) phase where four satellites are\nfinally available for computing the user position. In this\nphase, the analysis of the measurements and position\nvelocity and time (PVT) obtained from the IOV satellites\ncan provide insight into the potentialities of the Galileo\nsystem. A methodology is suggested for the analysis of the\nGalileo IOV pseudorange and pseudorange rates collected\nfrom the E1 and E5 frequencies. Several days of data were\ncollected and processed to determine figures of merit such\nas root mean square and maximum errors of the Galileo\nobservables. From the analysis, it emerges that Galileo is\nable to achieve better accuracy than GPS. A thorough\nanalysis of the PVT performance is also carried out using\nbroadcast ephemerides. Galileo and GPS PVTs are compared\nunder similar geometry conditions showing the\npotential of the Galileo system....
The continuous evolution of global navigation\nsatellite systems (GNSS) meteorology has led to an\nincreased use of associated observations for operational\nmodern low-latency numerical weather prediction (NWP)\nmodels, which assimilate GNSS-derived zenith total delay\n(ZTD) estimates. The development of NWP models with\nfaster assimilation cycles, e.g., 1-h assimilation cycle in the\nrapid update cycle NWP model, has increased the interest\nof the meteorological community toward sub-hour ZTD\nestimates. The suitability of real-time ZTD estimates\nobtained from three different precise point positioning\nsoftware packages has been assessed by comparing them\nwith the state-of-the-art IGS final troposphere product as\nwell as collocated radiosonde (RS) observations. The ZTD\nestimates obtained by BNC2.7 show a mean bias of\n0.21 cm, and those obtained by the G-Nut/Tefnut software\nlibrary show a mean bias of 1.09 cm to the IGS final troposphere\nproduct. In comparison with the RS-based ZTD,\nthe BNC2.7 solutions show mean biases between 1 and\n2 cm, whereas the G-Nut/Tefnut solutions show mean\nbiases between 2 and 3 cm with the RS-based ZTD, and the\nambiguity float and ambiguity fixed solutions obtained by\nPPP-Wizard have mean biases between 6 and 7 cm with\nthe references. The large biases in the time series from\nPPP-Wizard are due to the fact that this software has been\ndeveloped for kinematic applications and hence does not\napply receiver antenna eccentricity and phase center offset\n(PCO) corrections on the observations. Application of the\neccentricity and PCO corrections to the a priori coordinates\nhas resulted in a 66 % reduction of bias in the PPP-Wizard\nsolutions. The biases are found to be stable over the whole\nperiod of the comparison, which are criteria (rather than the\nmagnitude of the bias) for the suitability of ZTD estimates\nfor use in NWP nowcasting. A millimeter-level impact on\nthe ZTD estimates has also been observed in relation to\nambiguity resolution. As a result of a comparison with the\nestablished user requirements for NWP nowcasting, it was\nfound that both the G-Nut/Tefnut solutions and one of the\nBNC2.7 solutions meet the threshold requirements,\nwhereas one of the BNC2.7 solution and both the PPPWizard\nsolutions currently exceed this threshold...
Galileo, the European global navigation satellite\nsystem, is in its in-orbit validation phase and the four\nsatellites which have been available for some months now\nhave allowed a preliminary analysis of the system performance.\nPrevious studies have showed that Galileo will be\nable to provide pseudorange measurements more accurate\nthan those provided by GPS. However, a similar improvement\nwas not found for pseudorange rate observations\nin the velocity domain. This fact stimulated additional\nanalysis of the velocity domain, and, in particular, an unintended\noscillatory component was identified as the main\nerror source in the velocity solution. The magnitude of\nsuch oscillation is less than 10 cm/s, and its period is in the\norder of few minutes. A methodology was developed to\nidentify oscillatory components in the Galileo IOV pseudorange\nrate observables, and it was verified that the\nmeasurements from Galileo IOV PFM and Galileo IOV\nFM2 are affected by a small oscillatory disturbance. This\ndisturbance stems from the architecture adopted for combining\nthe frequency references provided by the two active\nclocks present in the Galileo satellites. The issue has been\nsolved in Galileo IOV FM3 and Galileo IOV FM4, and the\noscillatory component has been eliminated. We also propose\na methodology for removing this unwanted component\nfrom the final velocity solution and for determining\nthe performance that Galileo will be able to achieve. The\nanalysis shows that Galileo velocity solution will provide a\nroot-mean-square error of about 8 cm/s even in the limited\ngeometry conditions achieved using only four satellites.\nThis shows the potential of Galileo also in the determination\nof user velocity....
The International GNSS Service (IGS) realtime\nservice (RTS) provides access to real-time precise\nproducts such as orbits, clocks and code biases, which can\nbe used as a substitute for ultra-rapid products in real-time\napplications. The true performance of these products can be\nassessed by the Analysis Centers daily statistics derived\nfrom the comparison with IGS rapid products. Additionally,\nindirect verification is performed by their application\nto various precise point positioning strategies. Monitoring\nresults and basic descriptions of these products are available\nat the official RTS Web page (http://rts.igs.org/). We\npresent a more detailed description of RTS products.\nInformation from various sources is collected to provide\nproducts application methodology and describe their\nimportant features. We provide extended verification of the\nproducts using 1 week of real-time correction data. Results\nare presented separately for GNSS constellations, considering\nsatellite block and type of onboard clock. Comparison\nwith ESA/European Space Operations Centre final\nproducts proves the high accuracy of RTS orbits and\nclocks, which is 5 cm for GPS orbits, 8 cm for GPS clocks,\n13 cm for GLONASS orbits and 24 cm for GLONASS\nclocks. The real-time correction performance is also\nexamined regarding availability and latency. In general, the\navailability of corrections was beyond 95 % for GPS and\nbeyond 90 % for GLONASS. Since the increasing degradation\nof product quality with latency is critical for realtime\napplications, the relation between product latency and\naccuracy is analyzed. It confirms that high-rate stream\nupdate intervals are suitable for the data provided and that\nthe obsolete data should not be used. To avoid this, we\npropose a method of short-term prediction of RTS corrections\nthat extends the application period of obsolete\ncorrection data without a significant loss in orbit quality.\nUsing polynomial fitting, it is possible to forecast the orbit\ncorrections reliably up to 8 min for GPS and 4 min for\nGLONASS....
Precise navigation map is crucial in many fields. This paper proposes a panorama based method to detect and recognize lane\nmarkings and traffic signs on the road surface. Firstly, to deal with the limited field of view and the occlusion problem, this paper\ndesigns a vision-based sensing systemwhich consists of a surround viewsystemand a panoramic system. Secondly, in order to detect\nand identify traffic signs on the road surface, sliding window based detection method is proposed. Template matching method and\nSVM (Support Vector Machine) are used to recognize the traffic signs. Thirdly, to avoid the occlusion problem, this paper utilities\nvision based ego-motion estimation to detect and remove other vehicles.As surround viewimages contain less dynamic information\nand gray scales, improved ICP (Iterative Closest Point) algorithm is introduced to ensure that the ego-motion parameters are\nconsequently obtained. For panoramic images, optical flow algorithm is used.The results from the surround view system help to\nfilter the optical flow and optimize the ego-motion parameters; other vehicles are detected by the optical flow feature. Experimental\nresults show that it can handle different kinds of lane markings and traffic signs well....
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