Projecte llegit
Títol: Establishment of Sigma Ground for GBAS
Director/a: SANZ SUBIRANA, JAUME
Departament: MAT
Títol: Establishment of Sigma Ground for GBAS
Data inici oferta: 27042015 Data finalització oferta: 27122015
Estudis d'assignació del projecte:
Tipus: Individual  
Lloc de realització: 

Segon director/a (UPC): JUAN ZORNOZA, JOSÉ MIGUEL  
Paraules clau:  
GBAS , GNSS, GPS  
Descripció del contingut i pla d'activitats:  
The Ground based Augmentation System (GBAS) is being developed to enable precision approach and landing operations using the Global Positioning System (GPS). Each GBAS installation provides services through a GBAS Ground Facility (GGF) which is located at the airport it serves. By monitoring the GPS signals, measurements, and navigation messages, the GGF is able to exclude unhealthy satellites and broadcast realtime range correction messages for healthy satellites to users via a VHF data link. Airborne users apply these corrections to remove errors that are common between the GGF and the aircraft.
GBAS ground facility broadcast the pr_gnd parameter in the message Type 1, which is assumed as the standard deviation of the faultfree measurement error for each averaged pseudorange correction. This value is stablished when siting the station, and must describe the variance of a Gaussian distribution that bounds the total uncorrelated error contributions to the ground broadcast corrections. Indeed, the zeromean normal distribution with standard deviation pr_gnd must overbound the true cumulative error distribution, which in reality is not a necessary normal or zeromean. The target of this proposal is to implement the procedure defined in (B. Pervan et al., 2005) to estimate the pr_gnd using dualfrequency measurements and accounting for all different sources affecting this parameters. Objectives:  Background literature review to know the state of the Art.  To develop algorithms to estimate the receiver noise and multipath from code and carrier measurements from the GBAS receivers. To implement: o A binning method to select the sample size o Sigma inflation to account for the limited number of samples uncertainty o Sigma inflation to account for correlation between receivers.  To apply additional sigma inflation to account for seasonal effects.  To write a report summarising the work done and with a critical review of methodology and results. 

Overview (resum en anglès):  
The Ground based Augmentation System (GBAS) is being developed to enable precision approach and landing operations using the Global Positioning System (GPS). Each GBAS installation provides services through a GBAS Ground Facility (GGF) which is located at the airport it serves. By monitoring the GPS signals, measurements, and navigation messages, the GGF is able to exclude unhealthy satellites and broadcast realtime range correction messages for healthy satellites to users via a VHF data link. Airborne users apply these corrections to remove errors that are common between the GGF and the aircraft.
GBAS ground facility broadcast the pr_gnd parameter in the message Type 1, which is assumed as the standard deviation of the faultfree measurement error for each averaged pseudorange correction. This value is stablished when siting the station, and must describe the variance of a Gaussian distribution that bounds the total uncorrelated error contributions to the ground broadcast corrections. Indeed, the zeromean normal distribution with standard deviation pr_gnd must overbound the true cumulative error distribution, which in reality is not a necessary normal or zeromean. The target of this proposal is to implement the procedure defined in (B. Pervan et al., 2005) to estimate the pr_gnd using dualfrequency measurements and accounting for all different sources affecting this parameters. Objectives:  Background literature review to know the state of the Art.  To develop algorithms to estimate the receiver noise and multipath from code and carrier measurements from the GBAS receivers. To implement: o A binning method to select the sample size o Sigma inflation to account for the limited number of samples uncertainty o Sigma inflation to account for correlation between receivers.  To apply additional sigma inflation to account for seasonal effects.  To write a report summarising the work done and with a critical review of methodology and results. 