P7.7

**Estimation of radio refractivity structure using radar clutter**

L. Ted Rogers, Space and Naval Warfare Systems Center, San Diego, CA; and P. Gerstoft and J. L. Krolik

In radar meteorology, "anomalous propagation" (AP) clutter is usually viewed as a contaminant in the retrieval of information (e.g., rain rate) using Dopper radar. For naval forces, however, the characterization of the atmospheric refractivity structure that leads to AP clutter is important information as non-standard refractivity structures significantly change where targets can and cannot be seen using shipboard radars.

The refractivity structures of interest fall into two general categories: evaporation ducts that arise from the refractivity profile in the surface layer above bodies of water, and surface based ducts that are associated with an inversion layer. The inference of the evaporation duct from radar sea clutter is a fairly simple parameter estimation problem [see Rogers, Hattan and Stapleton, Estimating evaporation duct heights from radar sea echo, Radio Science, 35(4), 2000]. The inference of parameters characterizing surface based ducts, though, is a multi-parameter inverse problem. A conventional inverse problem approach is to cast the problem in the form

**E ^{*}**=arg

where **E** is a vector of global
environmental parameters (e.g., the trapping layer base-height (*z _{T}*),
change in refractivity across the inversion, etc.),

Presently, we have a mixture of results. We believe that most of the
poor results stem from range-dependency of the environmental parameters,
in particular, that of *z _{T}_{}_{}*.
This leads to shifting the range where features such as clutter rings
occur, a behavior that is problematic when the objective function f(

We demonstrate: (a) the success and a failure of the conventional
algorithm using range-independent parameters, (b) the sensitivity of the
clutter field to refractivity parameters whose changes in range are
modeled as a Markov process, (c) the use of conventional algorithm where
**E** has been augmented to include
parameters describing the range dependency of *z*_{T},
and (d)) the use of a non-linear recursive Bayesian state
estimation algorithm.

Poster Session 7, Algorithms—Data Quality

**Friday, 20 July 2001, 2:00 PM-3:30 PM**** Previous paper Next paper
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