Publication: Magyar Közlöny
Issue: MK-2007-70 (Year: 2007, Number: 70)
Era: 2004-2010
Section: Melléklet a 2007. évi XLVI. törvényhez
Paragraph Index: 3786

t) cos t sin t t d d d d ­ ½ ° ° ª º V ® ¾  V Z  Z t « » ° ° Z ¬ ¼ ¯ ¿ where Ȧd = 2ʌfd. 8.5.2 Threat Model B for GPS corresponding to second order anomalies uses the following ranges for the parameters ǻ, fd and ı: ǻ= 0; 4  fd  17; and 0.8  ı  8.8. Threat Model B for GLONASS corresponding to second order anomalies uses the following ranges for the parameters defined above: ǻ = 0; 10  fd  20; and 2  ı  8. 8.5.3 Within these parameter ranges, threat Model B generates distortions of the correlation peak as well as false peaks. 8.6 Threat Model C introduces both lead/lag and amplitude modulation. Specifically, it consists of outputs from a second order system when the C/A code signal at the input suffers from lead or lag. This waveform is a combination of the two effects described above. 8.6.1 Threat Model C for GPS includes parameters ǻ, fd and ıwith the following ranges: –0.12  ǻ  0.12; 7.3  fd  13; and 0.8  ı  8.8. Threat Model C for GLONASS includes parameters ǻ, fd and ı with the following ranges: –0.11  ǻ  0.11; 10  fd  20; and 2  ı  8. 8.6.2 Within these parameter ranges, threat Model C generates dead zones, distortions of the correlation peak and false peaks. 8.7 Unlike GPS and GLONASS, the SBAS signal is commissioned and controlled by the service provider. Moreover, the service provider also monitors the quality of the signal from the SBAS. To this end, the threat model will be specified and published by the service provider for each SBAS satellite. The SBAS SQM will be designed to protect all avionics that comply with Table D-12. Publication of the threat model is required for those cases where a service provider chooses to allow the SBAS ranging signal from a neighbouring service provider to be used for precision approach by SBAS or GBAS. In these cases, the service provider will monitor the SBAS ranging signal from the neighbouring satellite. 8.8 In order to analyse the performance of a particular monitor design, the monitor limit must be defined and set to protect individual satellite pseudo-range error relative to the protection level, with an allocation of the ground subsystem integrity risk. The maximum tolerable error (denoted as MERR) for each ranging source i can be definedin GBAS as: MERR = Kffmdıpr_gnd,i and ^ ` V,PA i,UDRE i,UIRE MERR=K min V  V 23/11/06 ATT D-44 2007/70/II. szám Attac ment Annex 10 — Aeronautical Communications for SBAS APV and precisionapproach where min ^ ` i,UIRE V is the minimum possiblevaluefor any user. MERR is evaluated at the output of a fault-free user receiver and varies with satellite elevation angle and ground subsystem performance. 8.9 The SQM is designed to limit the UDRE to values below the MERR in the case of a satellite anomaly. Typically, the SQM measures various correlation peak values and generates spacing and ratio metrics that characterize correlation peak distortion. Figure D-9 illustrates typical points at the top of a fault-free, unfiltered correlation peak. 8.9.1 A correlator pair is used for tracking. All other correlator values are measured with respect to this tracking pair. 8.9.2 Two types of test metrics are formed: early-minus-late metrics (D) that are indicative of tracking errors caused by peak distortion, and amplitude ratio metrics (R) that measure slope and are indicative of peak flatness or close-in, multiple peaks. 8.9.3 It is necessary that the SQM has a precorrelation bandwidth that is sufficiently wide to measure the narrow spacing metrics, so as not to cause significant peak distortion itself and not to mask the anomalies caused by the satellite failure. Typically, the SQM receiver must have a precorrelation bandwidth of at least 16 MHz for GPS and at least 15 MHz for GLONASS. 8.9.4 The test metrics are smoothed using low-pass digital filters. The time constant of these filters are to be shorter than those used jointly (and standardized at 100 seconds) by the reference receivers for deriving differential corrections and by the aircraft receiver for smoothing pseudo-range measurements (using carrier smoothing). The smooth metrics are then compared to thresholds. If any one of the thresholds is exceeded, an alarm is generated for that satellite. 8.9.5 The thresholds used to derive performance are defined as minimum detectable errors (MDEs) and minimum detectable ratios (MDRs). Fault-free false detection probability and missed detection probability are used to derive MDEs and MDRs. The noise in metrics (D) and (R), as denoted ıD,test and ıR,test below, is dominated by multipath errors. Note that the metric test can also have a mean value (µtest) caused by SQM receiver filter distortion. Threshold tests must also account for the mean values. 8.9.6 The MDE and MDR values used in the SQM performance simulations are calculated based on the following equations: MDE = (Kffd + Kmd) ıD,test and MDR = (Kffd + Kmd) ıR,test where Kffd = 5.26 is a typical fault-free detection multiplier representing a false detection probability of 1.5 u 10–7 per test; Kmd = 3.09 is a typical missed detection multiplier representing a missed detection probability of 10–3 per test;  ıD,test is the standard deviation of measured values of difference test metric D; and  ıR,test is the standard deviation of measured values of ratio test metric R. 8.9.7 If multiple independent SQM receivers are used to detect the failures, the sigma values can be reduced by the square root of the number of independent monitors. ATT D-45 23/11/06 2007/70/II. szám Annex 10 — Aeronautical Communications Volume I 8.9.8 A failure is declared if | D,test – µD,test |  MDE or | R,test – µR,test |  MDR for any of the tests performed, where µX,test is the mean value of the test X that accounts for fault-free SQM receiver filter distortion, as well as correlation peak distortion peculiar to the specific C/A code PRN. (Not all C/A code correlation peaks have the same slope. In a simulation environment, however, this PRN distortion can be ignored, and a perfect correlation peak can be used, except for simulated filter distortion.) 8.10 The standard deviations of the test statistics, ıD,test and ıR,test can be determined via data collection on a multicorrelator receiver in the expected operating environment. The data collection receiver utilizes a single tracking pair of correlators and additional correlation function measurement points which are slaved to this tracking pair, as illustrated in Figure D-9. Data is collected and smoothed for all available measurement points in order to compute the metrics. The standard deviation of these metrics define ıD,test. It is also possible to compute these one sigma test statistics if a multipath model of the installation environment is available. 8.10.1 The resulting ıD,test is highly dependent on the multipath environment in which the data are collected. The deviation due to multipath can be an order of magnitude greater than that which would result from noise even at minimum carrier-to-noise level. This aspect illustrates the importance of the antenna design and siting criteria which are the primary factors in determining the level of multipath that will enter the receiver. Reducing multipath will significantly decrease the resulting MDEs and thus improve the SQM capabilities. 8.10.2 Mean values µD,test and µR,test, on the other hand, are determined in a relatively error-free environment, such as through the use of GPS and GLONASS signal simulator as input. These mean values model the nominal SQM receiver’s filter distortion of the autocorrelation peak, including the effects of distortion due to adjacent minor autocorrelation peaks. The mean values can differ for the various PRNs based on these properties. 8.11 In order for the ground monitor to protect users against the different threat models described above, it is necessary to assume that aircraft receivers have specific characteristics. If no such constraints were assumed, the complexity of the ground monitor would be unnecessarily high. Evolution in the technology may lead to improved detection capability in the aircraft receiver and may alleviate the current constraints. 8.11.1 For double-delta correlators, the aircraft receiver tracks the strongest correlation peak over the full code sequence for every ranging source used in the navigation solution. 8.11.2 For double-delta correlators, the precorrelation filter rolls off by at least 30 dB per octave in the transition band. 8.11.3 The following parameters are used to describe the tracking performance specific to each type of satellite:

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