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RAIM: Difference between revisions
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==RAIM Concept== | ==RAIM Concept== | ||
Receiver Autonomous Integrity Monitoring (RAIM) can be defined as a user algorithm that determines the integrity of the GNSS solution. The RAIM algorithm compares the smoothed pseudorange measurements among themselves to ensure that they are all consistent. Basically, RAIM algorithms make use of measurements redundancy to check the relative consistency | Receiver Autonomous Integrity Monitoring (RAIM) can be defined as a user algorithm that determines the integrity of the GNSS solution. The RAIM algorithm compares the smoothed pseudorange measurements among themselves to ensure that they are all consistent. | ||
Basically, RAIM algorithms make use of measurements redundancy to check the relative consistency among them (by means of the residuals) and in case of detection, the most likely “failed” satellite is determined. A key assumption usually made in RAIM algorithms for civil aviation is that only one satellite may be faulty, i.e. the probability of multiple satellite failures is negligible. Another key issue related to RAIM algorithms is that one of their goals is to find measurement errors derived from non-nominal situations. | |||
Many [[RAIM Algorithms|RAIM algorithms]] follow these steps: | |||
*Preliminary step: Compute the navigation solution | *Preliminary step: Compute the navigation solution | ||
*Step 1: Fault detection Mechanism | *Step 1: Fault detection Mechanism | ||
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*5 visible satellites: if an anomaly is detected, the measurement from that specific satellite is discarded and therefore only 4 satellites are left. With only four satellites, the receiver does not have redundancy to compute the solution with different measurements and confirm that the solution is indeed correct. Therefore the receiver is able to issue a warning but not to provide integrity | *5 visible satellites: if an anomaly is detected, the measurement from that specific satellite is discarded and therefore only 4 satellites are left. With only four satellites, the receiver does not have redundancy to compute the solution with different measurements and confirm that the solution is indeed correct. Therefore the receiver is able to issue a warning but not to provide integrity | ||
*6 or more satellites: the receiver is able to detect and perform the exclusion | *6 or more satellites: the receiver is able to detect and perform the exclusion | ||
The more satellites in view, the more combinations of | |||
The more satellites in view, the more combinations of subsets of 4 satellites are available to detect potentially faulty satellites and the better the geometric observability. | |||
Please note that when the number of satellites in view increases, the assumption that the probability of multiple satellites is negligible can be questionable. | Please note that when the number of satellites in view increases, the assumption that the probability of multiple satellites is negligible can be questionable. | ||
==Summary== | ==Summary== | ||
Revision as of 14:32, 27 May 2011
| Fundamentals | |
|---|---|
| Title | RAIM |
| Author(s) | GMV |
| Level | Basic |
| Year of Publication | 2011 |
Civil aviation community imposes stringent requirements on the levels of precision, integrity, continuity of service and availability provided by GNSS. One of the most essential aspects relies on integrity and its impact on safety, the major driver in civil aviation. Integrity in GNSS is the capability of providing timely warnings to the user when the service should not be used. These drivers have pushed GNSS community to look for solutions that could guarantee integrity in the civil aviation domain.
Background
Integrity failures can be a consequence of anomalies coming from the space, user and control segment or system allocated SIS aberrations. The most common anomaly source reported during GPS operations was clock anomalies in the space segment. Another example that has been observed is carrier leakage in the spectrum[1]. Furthermore, since ground control segments of legacy GNSS did not have full time satellite visibility, an anomaly in one of the satellites could take up to a few hours to be identified and disseminated by the control segment.
Under the GPS Standard Positioning Service (SPS) specifications, the probability of failure is approximately 10-4 per hour, whereas a number of operations require integrity risk to be bounded by 10-7 per hour[2]. In this context, integrity monitoring functions would have to detect failures at the level of 10-3 per hour in order to meet the civil aviation requirements.
Although pushed by the civil aviation community, it should be noted that the integrity concept and related algorithms have also been identified as required by other segments, such as liability critical applications[3], e.g. road tolling.
Integrity Architectures
The main driver pushing GNSS for integrity comes from the aeronautical domain, for which integrity is a critical requirement, since any failure could lead to losses of lives.
Three different architectures have been proposed to provide integrity to the aviation community[4]:
- SBAS
The Satellite-Based Augmentation System (SBAS) is a differential technique that relies on geostationary satellites to broadcast the augmentation information (e.g. corrections and integrity-related). In addition, SBAS also provides ranging capabilities, thus potentially increasing satellite availability. Being GEO satellites, SBAS coverage is limited to a regional area, e.g. EGNOS in EU or WAAS in US, and currently only supports APV I or II approaches.
- GBAS
Ground-Based Augmentation Systems (GBAS) provides GNSS augmentation based on local ground elements. GBAS is a differential technique in which augmentation information (e.g. corrections and integrity-related information) is transmitted to the receiver via Very High Frequency Data Broadcast (VDB) and therefore it can be used in airports (coverage of around 30 km) for CAT III operations.
- ABAS
Unlike the remaining augmentation systems, Aircraft-Based Augmentation System (ABAS) focuses on integrity only, and not on improving solution accuracy (i.e. no corrections are provided). ABAS supports Non Precision Approaches using GPS L1 and it is mainly limited by the vertical error component.
Within ABAS, two types of techniques are envisaged[4]:
- Receiver Autonomous Integrity Monitoring (RAIM), where only GNSS information is used. RAIM scheme can be included in the satellite navigation airborne equipment, either as the main source of integrity or as a back-up for alternative sources, e.g. SBAS.
- Airborne Autonomous Integrity Monitoring (AAIM), where GNSS information is complemented with on-board sensors and other components
RAIM Concept
Receiver Autonomous Integrity Monitoring (RAIM) can be defined as a user algorithm that determines the integrity of the GNSS solution. The RAIM algorithm compares the smoothed pseudorange measurements among themselves to ensure that they are all consistent.
Basically, RAIM algorithms make use of measurements redundancy to check the relative consistency among them (by means of the residuals) and in case of detection, the most likely “failed” satellite is determined. A key assumption usually made in RAIM algorithms for civil aviation is that only one satellite may be faulty, i.e. the probability of multiple satellite failures is negligible. Another key issue related to RAIM algorithms is that one of their goals is to find measurement errors derived from non-nominal situations.
Many RAIM algorithms follow these steps:
- Preliminary step: Compute the navigation solution
- Step 1: Fault detection Mechanism
- Step 2: Isolation of “faulty” satellites
- Step 3: Protection levels computation (although this step may be optional)
Taking into account that the user needs to solve four unknowns (3D position and clock) from the satellites, it follows that:
- 4 visible satellites are not enough to provide integrity
- 5 visible satellites: if an anomaly is detected, the measurement from that specific satellite is discarded and therefore only 4 satellites are left. With only four satellites, the receiver does not have redundancy to compute the solution with different measurements and confirm that the solution is indeed correct. Therefore the receiver is able to issue a warning but not to provide integrity
- 6 or more satellites: the receiver is able to detect and perform the exclusion
The more satellites in view, the more combinations of subsets of 4 satellites are available to detect potentially faulty satellites and the better the geometric observability.
Please note that when the number of satellites in view increases, the assumption that the probability of multiple satellites is negligible can be questionable.
Summary
Summarizing, the key features of RAIM algorithms are:
- Basic hypothesis: only one satellite is “faulty”, probability of multiple satellite failures at the same time is considered negligible
- Number of satellites in view determines the possibility of providing integrity
- Protection levels size depend on satellite geometry (DOP)
- RAIM algorithms use code measurements
The navigation performances of a typical RAIM are:
- Integrity Risk: configured to the desired value and depends on the application
- HPLs and VPLs: if the integrity risk is configured to 10-7 , the values of PLs are higher than the ones provides by a SBAS
- The concept of TTA is meaningless for RAIM algorithms: if the fault detection mechanism (step 1 mentioned above) detects any failure, that measurement is not considered to obtain the position solution. That is, the alert time is zero, the detection is immediate.
Related articles
References
- ^ Kaplan, E.D. et al, "Understanding GPS: Principles and Applications", second edition
- ^ Y. Lee, K. Van Dyke, B. DeCleene, J. Studenny, M. Beckmann, Summary of RTCA SC-159 GPS Integrity Working Group Activities. Navigation Vol. 43, No 3, 1996
- ^ "Autonomous Integrity, an Error Isotropy Based Approach for Multiple Fault Conditions", M. Azaola, J. Cosmen, InsideGNSS, 2009, http://www.insidegnss.com/auto/janfeb09-azaoli.pdf
- ^ a b ICAO Standard and Recommended Procedures (SARPS) Annex 10