The emergence of data bases for the management of hydrographic data raises some questions about how to characterize the quality of data pla'ced in the data base. This is important, since subsequent automatic hand1in.g of the data will be less dependent on the human "feel" for data quality that has been the case in the past.In this paper we review approaches that can be taken to olbtain data quality parameters for navigational data. In particular, those based ton various statistical assumptions are described and compared. Proposals for various options are presented.
The Bi‐normal density distribution function on a surface is represented by a position vector and covariance matrix. Its physical dimensions are described by the error ellipse. A generalized scalar is the radial or circular error which denotes the probability within a radius of the position. To compute the radial error probability (or probability circle) precisely, a non‐trivial numerical integration is necessary. Simpler but less accurate conventions in common use are the Drms and CEP. The error ellipse semi‐major axis is also sometimes applied to radial error. These three measures of radial error are subject to variations in probability as a function of the eccentricity of the distribution. The probability of a circle can be obtained simply and more accurately by the use of a third order polynomial.
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