A new daily of constant false alarm rate (CFAR) processors is introduced. An Ll-CFAR forms its noise power estimate by linearly filtering ranked samples from the reference set: the weights of this combination, however, depend not only on the rank, but also on the relative proximity of the sample to the cell under test. From the class of Ll-CFARs may be chosen members that effectively censor spurious targets, members that exhibit impressive control of false alarm in the presence of a clutter edge, and members that are robust against both such inhomogeneities. While the design of such schemes is involved, their implementation is not significantly more burdensome than that of plain order statistic (OS)-CFAR.

Adaptive detection via Ll-filters

LOPS, Marco;
1992

Abstract

A new daily of constant false alarm rate (CFAR) processors is introduced. An Ll-CFAR forms its noise power estimate by linearly filtering ranked samples from the reference set: the weights of this combination, however, depend not only on the rank, but also on the relative proximity of the sample to the cell under test. From the class of Ll-CFARs may be chosen members that effectively censor spurious targets, members that exhibit impressive control of false alarm in the presence of a clutter edge, and members that are robust against both such inhomogeneities. While the design of such schemes is involved, their implementation is not significantly more burdensome than that of plain order statistic (OS)-CFAR.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11580/21060
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