Application of Least-Squares Variance Component Estimation to GPS Observables

Amiri-Simkooei, A. R.; Teunissen, Peter; Tiberius, C.C.J.M.

doi:10.1061/(asce)0733-9453(2009)135:4(149)

Cited by 115 publications

(106 citation statements)

References 32 publications

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“…According to Teunissen (2000) and Amiri-Simkooei (2007), this test helps us study whether the functional and the stochastic models are properly selected. In this section, the latter (stochastic model) is focused on.…”

Section: Resultsmentioning

confidence: 99%

Incorporation of the GPS satellite ephemeris covariance matrix into the precise point positioning

Shirazian

2013

Journal of Geodetic Science

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Abstract:In GPS positioning, usually the satellite ephemeris are fixed in the observation equations using broadcast or published values. Therefore, to have a realistic covariance matrix for the observations one must incorporate a well-defined covariance matrix of the satellite ephemeris into the observations covariance matrix. Contributions so far have discussed only the variance and covariance of the observations. Precise Point Positioning (PPP) is a technique aimed at processing of measurements from a single (stand-alone) GPS receiver to compute high-accurate position. In this paper, the covariance matrix of the satellite ephemeris and its impact on the position estimates through the PPP are discussed. Keywords

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Section: Resultsmentioning

confidence: 99%

Incorporation of the GPS satellite ephemeris covariance matrix into the precise point positioning

Shirazian

2013

Journal of Geodetic Science

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“…A realistic stochastic model for DD GPS observables is of the form (Amiri-Simkooei et al, 2009, 2013 The …”

Section: A Realistic Stochastic Modelmentioning

confidence: 99%

“…Therefore, it still remains necessary to investigate rigorous methods for constructing a more reliable covariance matrix of the GPS observables. An appropriate stochastic model for GPS observables may include different variances for each observation type, the correlation among different observables, the satellite elevation dependence of observables precision, and the possible temporal correlation of the GPS observables (Amiri-Simkooei et al, 2009, 2013. Therefore, we first define a general form of the covariance matrix of the GPS observables, which includes the abovementioned variance and covariance components into the stochastic model.…”

Section: Introdctionmentioning

confidence: 99%

“…LS-VCE was originally developed by Teunissen (1988). Further elaboration and development of the LS-VCE are provided by Teunissen and Amiri-Simkooei (2008) and Amiri-Simkooei (2007). The geometry-based observation model (GBOM), employed as the functional model, is the widely used mathematical model for high precision GPS positioning from code and phase observations using a relative GPS receiver setup (Odijk, 2008).…”

Section: Introdctionmentioning

confidence: 99%

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On the Realistic Stochastic Model of GPS Observables: Implementation and Performance

Zangeneh-Nejad

Amiri-Simkooei

Sharifi

et al. 2015

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:High-precision GPS positioning requires a realistic stochastic model of observables. A realistic GPS stochastic model of observables should take into account different variances for different observation types, correlations among different observables, the satellite elevation dependence of observables precision, and the temporal correlation of observables. Least-squares variance component estimation (LS-VCE) is applied to GPS observables using the geometry-based observation model (GBOM). To model the satellite elevation dependent of GPS observables precision, an exponential model depending on the elevation angles of the satellites are also employed. Temporal correlation of the GPS observables is modelled by using a first-order autoregressive noise model. An important step in the high-precision GPS positioning is double difference integer ambiguity resolution (IAR). The fraction or percentage of success among a number of integer ambiguity fixing is called the success rate. A realistic estimation of the GNSS observables covariance matrix plays an important role in the IAR. We consider the ambiguity resolution success rate for two cases, namely a nominal and a realistic stochastic model of the GPS observables using two GPS data sets collected by the Trimble R8 receiver. The results confirm that applying a more realistic stochastic model can significantly improve the IAR success rate on individual frequencies, either on L1 or on L2. An improvement of 20% was achieved to the empirical success rate results. The results also indicate that introducing the realistic stochastic model leads to a larger standard deviation for the baseline components by a factor of about 2.6 on the data sets considered.* Corresponding author INTRODCTIONGPS data processing is usually performed by the least squares adjustment method for which both the functional and stochastic models must be correctly specified. The functional model, describing the mathematical relation between the observations and the unknown parameters, is usually well known either in the relative positioning or in the single/precise point positioning (Seeber, 2003;Hofmann-Wellenhof et al., 2008;Leick, 2004; Teunissen and Kleusberg, 1998;Rizos, 1997). However, the stochastic model, expressing the statistical characteristics of the GPS observations by means of a covariance matrix, is still a challenging problem. Misspecification in the stochastic model leads to unreliable and suboptimal estimates. The realistic stochastic model should thus be utilized aiming at obtaining reliable least squares estimates.There are a few common stochastic models for GPS observables: (1) Equal-weight stochastic model in which identical variances for each measurement type are chosen (i.e. the same variance for the code and the same variance for the phase observations). This structure ignores the correlations among different observables, (2) Satellite elevation-angle dependent model in which the observations weighting procedure is performed using trigonometric or exponential functions. T...

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“…Para comprobar las relaciones entre el e − IT GC y los factores institucionales formales, se realizó el análisis de regresión múltiple. Se adoptó el método de mínimos cuadrados ordinarios con el estimador de los componentes de la varianza (LS-VCE).Éste es considerado un método robusto que estima los componentes de la (co)varianza de forma lineal y permite obtener estimadores no sesgados (Amiri-Simkooei, 2007). El modelo en sí se derivó de la agregación de los cuatro sub-índices del e − IT GC, la variables del sistema legal y de gobierno corporativo (tamaño y composición del consejo, dualidad COB-CEO, participación femenina del consejo, presencia del comité de auditoría y concentración de la propiedad), así como las variables de control corporativas (tamaño y edad de la empresa, ROA, endeudamiento, y sector industrial).…”

Section: Análisis Univariante Y Multivariableunclassified

Factores que Inciden en una Mayor Transparencia de Gobernanza Corporativa en Empresas Cotizadas Latinoamericanas

Turrent¹

2014

REMEF

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ResumenBajo el enfoque de la teoría institucional, nuestro trabajo realiza un estudio comparativo del nivel de transparencia en gobierno corporativo de empresas cotizadas Latinoamericanas en el periodo de 2004-2010. Por otro lado, identifica aquellos factores institucionales formales que inciden en la transparencia de gobernanza empresarial. Los resultados ponen de manifiesto que el sistema legal, el tamaño y composición del consejo, la presencia del comité de auditoría, el tamaño de la empresa, el nivel de endeudamiento y el sector industrial inciden significativamente en el nivel de transparencia en gobierno corporativo en la región Latinoamericana. AbstractUnder the institutional theory approach, our work aims to obtain a comparative study of corporate governance transparency level on Latin American listed companies during 2004-2010 period. On the other hand, to identify those formal institutional factors that have a significant influence on corporate governance disclosure. The results indicate that legal system, board size, board composition, audit committee, size of the company, leverage, and industry type influence on corporate governance transparency on Latin American region.

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Application of Least-Squares Variance Component Estimation to GPS Observables

Cited by 115 publications

References 32 publications

Incorporation of the GPS satellite ephemeris covariance matrix into the precise point positioning

Incorporation of the GPS satellite ephemeris covariance matrix into the precise point positioning

On the Realistic Stochastic Model of GPS Observables: Implementation and Performance

Factores que Inciden en una Mayor Transparencia de Gobernanza Corporativa en Empresas Cotizadas Latinoamericanas

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