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• W2034014706 abstract "S u m m a r y termine for instance whether it is there and if yes where it is. This is the case also when one wishes to determine which one We present a procedure for determining the location of an underground object from scattering data. The procedure assumes that the object is known and that its location is to be estimated from an arbitrary (small) number of noisy scattering experiments. The procedure is not limited to a particular measurement geometry and is particularly suited to geophysical problems where the cost per experiment puts a limit on the amount of available data, a situation that we refer to as the data-poor case. The procedure consists of computing the log likelihood image of the object location, the location of the peak of which is the estimate of the location of the object location. The log likelihood image is shown to consist of a weighted summation of several sub-images, the weighting factors of which are determined by the data. Each sub-image depends on the exact geometry of one experiment used for collecting the data and can be precomputed such that the estimation process can be carried out in real time and recursively, meaning that the log likelihood image is built progressively with the process of data collection. An a-priori decision upon the number of experiments necessary for estimating the location of an object does not have therefore to be made. Based on intermediate log likelihood images it can be decided whether a reliable estimate can be made or more experiments are necessary. of a group of possible targets (hypotheses in the terminology of the signal processing community) is there or when one knows the target shape and only does not know its contrast with respect to the surrounding and/or its size scale. Usually there is no known way to integrate this a-priori knowledge into the imaging algorithm and it is left to the (human) interpreter to use it when interpreting a low quality image. In this case the imaging approach appears to be inefficient and an alternative approach that focuses only on the sought information and uses much less data is more appropriate. One such alternative approach is that of target detection and parameter estimation and is the subject of this paper. Stated in a simplified manner, in this (maximum likelihood) approach the scattering data are compared (correlated) with the scattering data that would be measured for each of the hypothesized underground structures or objects and the hypothesis that corresponds to the highest correlation is decided to be the correct one. The hypotheses can be discrete like the presence or nonpresence of one particular underground object from a collection of possible objects, or continuous like the coordinates of the location of a particular object. In order to implement this approach one needs to compute (or measure in a test site) the scattered signal for every one of the hypotheses and perform a" @default.
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• W2034014706 date "1995-01-01" @default.
• W2034014706 modified "2023-09-26" @default.
• W2034014706 title "Maximum likelihood estimation of target location in acoustic and electromagnetic imaging" @default.
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• W2034014706 doi "https://doi.org/10.1190/1.1887557" @default.
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