1,723,122 research outputs found
RAIM Algorithms Analysis for a Combined GPS/GALILEO Constellation
No full textHow far a user can rely on his navigation system is
a central question for safety of life applications like air
navigation especially in approach phases. For Oceanic,
En route or Non Precision Approach phases, the integrity
requirements as defined by the ICAO (International Civil
Aviation Organization) should be fulfilled by the future
Galileo Safety of Life Service.
This paper presents the performances of RAIM algorithms
using a covariance matrix of a single frequency absolute
positioning receiver noise calculated using one year
measurement data.
In the configuration of combined GPS/GALILEO constellation,
the user will have the possibility to track at
least 10 satellites at the same time. This high availability
of satellites will provide a high availability of RAIM
algorithms.
The original approach used in this paper is to use the IPRE
(Instantaneous Pseudo Range Error) developed in [1] as
the input parameter of the RAIM algorithms. This concept
provides a generalized covariance matrix of pseudo range
noise taking into account correlations of pseudo range
errors with close elevation and azimuth angles. Thanks
to a Cholesky decomposition, it is always possible to use
the classical χ2 distribution to obtain the fault detection
threshold. The advantage of generalizing the RAIM
methods is not only in the simplicity of the algorithm, but
it is also in its efficiency thanks to lower protection levels
obtained
Cynthia Raim and David Allen Wehr in a Faculty and Guest Artist Recital
No full textThis is the program for the recital of guest artist Cythina Raim and artist-in-residence and pianist David Allen Wehr, featuring works by Rachmaninoff. This recital took place on March 3, 1997, in the W. Francis McBeth Recital Hall
Advanced RAIM Architecture Design and User Algorithm Performance in a real GPS, GLONASS and Galileo scenario
No full textFailure Detection and Exclusion via Range Consensus
No full textWith the rise of enhanced GNSS services over the next decade (i.e. the modernized GPS, Galileo, GLONASS, and Compass constellations), the number of ranging sources (satellites) available for a positioning will significantly increase to more than double the current value. One can no longer assume that the probability of failure for more than one satellite within a certain timeframe is negligible. To ensure that satellite failures are detected at the receiver is of high importance for the integrity of the satellite navigation system. With a large number of satellites, it will be possible to reduce multipath effects by excluding satellites with a pseudorange bias above a certain threshold. The scope of this work is the development of an algorithm that is capable of detecting and identifying all such satellites with a bias higher than a given threshold.
The Multiple Hypothesis Solution Separation (MHSS) RAIM Algorithm (Ene, 2007; Pervan, et al., 1998) is one of the existing approaches to identify faulty satellites by calculating the Vertical Protection Level (VPL) for subsets of the constellation that omit one or more satellites. With the aid of the subset showing the best (or minimum) VPL, one can expect to detect satellite faults if both the ranging error and its influence on the position solution are significant enough. At the same time, there are geometries and range error distributions where a different satellite, other than the faulty one, can be excluded to minimize the VPL. Nevertheless, with multiple constellations present, one might want to exclude the failed satellite, even if this does not always result in the minimum VPL value, as long as the protection level stays below the Vertical Alert Limit (VAL).
The Range Consensus (RANCO) algorithm, which is developed in this work, calculates a position solution based on four satellites and compares this estimate with the pseudoranges of all the satellites that did not contribute to this solution. The residuals of this comparison are then used as a measure of statistical consensus. The satellites that have a higher estimated range error than a certain threshold are identified as outliers, as their range measurements disagree with the expected pseudoranges by a significant amount given the position estimate. All subsets of four satellites that have an acceptable geometric conditioning with respect to orthogonality will be considered. Hence, the chances are very high that a subset of four satellites that is consistent with all the other “healthy” satellites will be found. The subset with the most inliers is consequently utilized for identification of the outliers in the combined constellation.
This approach allows one to identify as many outliers as the number of satellites in view minus four satellites for the estimation, and minus at least one additional satellite, that confirms this estimation. As long as more than four plus at least one satellites in view are consistent with respect to the pseudoranges, one can reliably exclude the ones that have a bias higher than the threshold. This approach is similar to the Random Sample Consensus Algorithm (RANSAC), which is applied for computer vision tasks (Fischler, et al., 1981), as well as previous Range Comparison RAIM algorithms (Lee, 1986). The minimum necessary bias in the pseudorange that allows RANCO to separate between outliers and inliers is smaller than six times the variance of the expected error. However, it can be made even smaller with a second variant of the algorithm proposed in this work, called Suggestion Range Consensus (S-RANCO). In S-RANCO, the number of times when a satellite is not an inlier of a set of four different satellites is computed. This approach allows the identification of a possibly faulty satellite even when only lower ranging biases are introduced as an effect of the fault.
The batch of satellite subsets to be examined is preselected by a very fast algorithm that considers the alignment of the normal vectors between the receiver and the satellite (first 3 columns of the geometry matrix). Concerning the computational complexity, only 4 by 4 matrices are being inverted as part of both algorithms. With the reliable detection and identification of multiple satellites producing very low ranging biases, the resulting information will also be very useful for existing RAIM Fault Detection and Elimination (FDE) algorithms (Ene, et al., 2007; Walter, et al., 1995)
Advanced RAIM Algorithms: First Results
No full textInternational audienceReceiver Autonomous Integrity Monitoring (RAIM) with detection/ exclusion functions is currently a major technique for the GNSS in many safety-critical civil aviation applications. Although RAIM algorithms are not directly standardized, most existing implementations are based (or equivalent to) a snapshot technique based on the least squares (LS) algorithm. The principal limitation of these conventional RAIM algorithms is the availability of detection and especially exclusion functions. This problem becomes crucially important when the RAIM has to be used to provide integrity for the vertical positioning information (for example to support APV I & II approaches). Therefore DGAC/STNA has sponsored UTT to conduct a study to investigate the potential benefits of more advanced RAIM algorithms to support APV operations. First, a statistical model of the position failure detection and exclusion based on RTCA high level definitions is defined. This model provides us with a mathematically formalized description of different events, which is important for further RAIM’s algorithm design, optimization and comparison. A formalized definition of a horizontal/vertical error that must be considered as a positioning failure has been proposed. This definition is used to compute for each epoch and for each satellite channel a pseudorange bias that leads to a positioning (horizontal/vertical) failure. A very special attention has been paid in this study to estimate the impact of the pseudorange autocorrelation function, due to the “tropo" and “iono" refraction, on the statistical performance (and availability) of RAIM schemes. No result is really available in the literature on this problem, which is crucially important for new types of high accuracy channels (like GPS L1/L5 or Galileo E1/E5). Next, we briefly introduce and describe two new RAIM detection/exclusion algorithms: snapshot RAIM algorithm based on the constrained Generalized Likelihood Ratio Test (GLRT); sequential RAIM algorithm based on the constrained GLRT. We also use the principle of pre-filtering in order to improve the signal-tonoise ratio of the faults. Finally, we analyze and compare the performance of the conventional LS-based RAIM detection/ exclusion solution with the proposed snapshot and sequential constrained GLRT-based algorithms with and without pre-filtering
Advanced RAIM Algorithms: First Results
No full textInternational audienceReceiver Autonomous Integrity Monitoring (RAIM) with detection/ exclusion functions is currently a major technique for the GNSS in many safety-critical civil aviation applications. Although RAIM algorithms are not directly standardized, most existing implementations are based (or equivalent to) a snapshot technique based on the least squares (LS) algorithm. The principal limitation of these conventional RAIM algorithms is the availability of detection and especially exclusion functions. This problem becomes crucially important when the RAIM has to be used to provide integrity for the vertical positioning information (for example to support APV I & II approaches). Therefore DGAC/STNA has sponsored UTT to conduct a study to investigate the potential benefits of more advanced RAIM algorithms to support APV operations. First, a statistical model of the position failure detection and exclusion based on RTCA high level definitions is defined. This model provides us with a mathematically formalized description of different events, which is important for further RAIM’s algorithm design, optimization and comparison. A formalized definition of a horizontal/vertical error that must be considered as a positioning failure has been proposed. This definition is used to compute for each epoch and for each satellite channel a pseudorange bias that leads to a positioning (horizontal/vertical) failure. A very special attention has been paid in this study to estimate the impact of the pseudorange autocorrelation function, due to the “tropo" and “iono" refraction, on the statistical performance (and availability) of RAIM schemes. No result is really available in the literature on this problem, which is crucially important for new types of high accuracy channels (like GPS L1/L5 or Galileo E1/E5). Next, we briefly introduce and describe two new RAIM detection/exclusion algorithms: snapshot RAIM algorithm based on the constrained Generalized Likelihood Ratio Test (GLRT); sequential RAIM algorithm based on the constrained GLRT. We also use the principle of pre-filtering in order to improve the signal-tonoise ratio of the faults. Finally, we analyze and compare the performance of the conventional LS-based RAIM detection/ exclusion solution with the proposed snapshot and sequential constrained GLRT-based algorithms with and without pre-filtering
Advanced RAIM Algorithms: First Results
No full textInternational audienceReceiver Autonomous Integrity Monitoring (RAIM) with detection/ exclusion functions is currently a major technique for the GNSS in many safety-critical civil aviation applications. Although RAIM algorithms are not directly standardized, most existing implementations are based (or equivalent to) a snapshot technique based on the least squares (LS) algorithm. The principal limitation of these conventional RAIM algorithms is the availability of detection and especially exclusion functions. This problem becomes crucially important when the RAIM has to be used to provide integrity for the vertical positioning information (for example to support APV I & II approaches). Therefore DGAC/STNA has sponsored UTT to conduct a study to investigate the potential benefits of more advanced RAIM algorithms to support APV operations. First, a statistical model of the position failure detection and exclusion based on RTCA high level definitions is defined. This model provides us with a mathematically formalized description of different events, which is important for further RAIM’s algorithm design, optimization and comparison. A formalized definition of a horizontal/vertical error that must be considered as a positioning failure has been proposed. This definition is used to compute for each epoch and for each satellite channel a pseudorange bias that leads to a positioning (horizontal/vertical) failure. A very special attention has been paid in this study to estimate the impact of the pseudorange autocorrelation function, due to the “tropo" and “iono" refraction, on the statistical performance (and availability) of RAIM schemes. No result is really available in the literature on this problem, which is crucially important for new types of high accuracy channels (like GPS L1/L5 or Galileo E1/E5). Next, we briefly introduce and describe two new RAIM detection/exclusion algorithms: snapshot RAIM algorithm based on the constrained Generalized Likelihood Ratio Test (GLRT); sequential RAIM algorithm based on the constrained GLRT. We also use the principle of pre-filtering in order to improve the signal-tonoise ratio of the faults. Finally, we analyze and compare the performance of the conventional LS-based RAIM detection/ exclusion solution with the proposed snapshot and sequential constrained GLRT-based algorithms with and without pre-filtering
Snapshot RAIM algorithms availability in urban areas
No full textThis paper presents some theoretical considerations concerned usage of Snapshot RAIM algorithms in city navigation. Influence of urban areas on RAIM Availability and Approximate Radial-Error Protected (ARP) is taken into consideration. Some results of numerical experiments are presented, too
RAIM 알고리즘을 이용한 GNSS/기압고도계 센서 융합 항법의 무결성 감시
No full text학위논문(석사) - 한국과학기술원 : 항공우주공학과, 2017.2,[v, 59 p. :]As the number of unmanned aircraft system (UAS) applications in the low-altitude civilian airspace increases, UAS traffic management (UTM) becomes vital to prevent unmanned aerial vehicles (UAVs) from collisions with the surrounding terrain, buildings and/or other vehicles. One feasible technology to accomplish UTM is receiver autonomous integrity monitoring (RAIM). RAIM is a Global Navigation Satellite System (GNSS)-receiver onboard system which can autonomously detect faults in measurements and produce protection levels in real time. The performance of RAIM is expected to be improved significantly due to the advent of GNSS multi-constellation and multi-frequency environments in the near future.
In this thesis, we developed RAIM for UAVs which use sensor integration with a standalone Global Positioning System (GPS) and a low-cost micro-electromechanical system (MEMS)-based barometer for their navigation. First, we developed a snapshot residual-based RAIM and analyzed the vertical protection level (VPL) performance for GPS/barometer-integrated navigation. To do this, we defined statistical overbounding models of errors in GPS pseudoranges and barometer measurements. For the GPS/barometer-integrated RAIM, we modified the original residual-based RAIM to consider the nominal bias of a barometer in a fault detection algorithm and VPL equations. Through this analysis, we found that the GPS/barometer integration makes RAIM performance more robust to the satellite geometry compared to the standalone GPS.
However, VPLs produced by the multisensory RAIM are still conservative because the system could not fully consider the different features of each sensor. For this reason, we proposed a new RAIM architecture termed residual-based-solution-separation (RB-SS) RAIM, representing the hybridization of a residual-based and a solution separation RAIM algorithm. Furthermore, we optimized integrity risk allocation to minimize VPLs. The proposed RAIM algorithm is beneficial in that it can exclude faulty sensors without greatly increased computational costs even under a GNSS multi-constellation environment while also effectively eliminating the conservativeness of the VPLs.한국과학기술원 :항공우주공학과
Calculation of RAIM Function Availability Based on GPS Constellation Configuration
No full textU završnom radu opisat de se uloga i važnost GPS-a u zrakoplovnoj navigaciji te zrakoplovni sustav dopune u obliku RAIM algoritma. Bit de prikazane navigacijske specifikacije u različitim segmentima i fazama leta te specifični zahtjevi performansi koje zrakoplov treba ispuniti da bi mogao letjeti u skladu s PBN konceptom. Također, detaljnije de biti definiran problem integriteta navigacijske poruke, uz prikaz izvora pogrešaka i sustava dopune satelitskih navigacijskih sustava. Bit de opisan i temeljni RAIM algoritam i tri osnovne RAIM sheme. Na kraju završnog rada opisat de se ukratko MATLAB program koji izračunava dostupnost funkcije RAIM i prikazat de se rad istoga na primjeru.In this paper role and importance of GPS in air navigation and aircraft-based augmentation system in the shape of RAIM algorithm will be described. Navigation specification in different segments and phases of flight will be presented, and specific performance requirements that must be carried out by the aircraft so that it can fly in accordance with PBN concept will be explained. Also, the integrity problem will be defined more in detail, along with error sources in GPS and review of augmentation systems. A baseline RAIM algorithm and three basic RAIM methods will be described. At the end of the paper MATLAB program which calculates RAIM function availability will be presented
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