[1] This paper describes estimation of low-altitude atmospheric refractivity from radar sea clutter observations. The vertical structure of the refractive environment is modeled using five parameters, and the horizontal structure is modeled using six parameters. The refractivity model is implemented with and without an a priori constraint on the duct strength, as might be derived from soundings or numerical weather-prediction models. An electromagnetic propagation model maps the refractivity structure into a replica field. Replica fields are compared to the observed clutter using a squared-error objective function. A global search for the 11 environmental parameters is performed using genetic algorithms. The inversion algorithm is implemented on S-band radar sea-clutter data from Wallops Island, Virginia. Reference data are from range-dependent refractivity profiles obtained with a helicopter. The inversion is assessed (1) by comparing the propagation predicted from the radar-inferred refractivity profiles and from the helicopter profiles, (2) by comparing the refractivity parameters from the helicopter soundings to those estimated, and (3) by examining the fit between observed clutter and optimal replica field. This technique could provide near-real-time estimation of ducting effects. In practical implementations it is unlikely that range-dependent soundings would be available. A single sounding is used for evaluating the radar-inferred environmental parameters. When the unconstrained environmental model is used, the ''refractivity-from-clutter,'' the propagation loss generated and the loss from this single sounding, is close within the duct; however, above the duct they differ. Use of the constraint on the duct strength leads to a better match also above the duct.

Abstract. The evaporation duct is a downward refracting layer that results from the rapid decrease in humidity with respect to altitude occurring in the atmospheric surface layer above bodies of water. The evaporation duct affects radar detection ranges at frequencies of approximately 1 GHz and above. Models based on Monin-Obukhov similarity theory are usually used to calculate evaporation duct refractivity profiles from bulk measurements of air temperature, humidity, wind speed, and the sea surface temperature. Modeling results by Pappert et al. [1992] indicated that the falloff of radar sea echo as a function of range was an increasing function of the evaporation duct height. On the basis of those results, the authors proposed inferring the evaporation duct height by a slope fit to modeled clutter power, a nonlinear least squares inversion procedure. Data for testing the inversion procedure were obtained using the S band Space Range Radar at Wallops Island, Virginia. Evaporation duct heights were inferred from the radar data on the basis of the assumption of a range-independent evaporation duct height and sea clutter radar cross section (o-ø). Validation data consist of buoy and boat in situ bulk measurements. The result of comparing the radar-inferred evaporation duct heights and those calculated from bulk measurements indicates that the radar-inferred duct heights are strongly correlated with those from the in situ measurements, but there is some uncertainty as to whether they are biased or unbiased. That uncertainty arises from the assumed dependence of o -ø on the grazing angle ½. That ½ dependence is currently a matter of debate in the open literature, with the lower and upper ends of modeling results being o.O • ½0 and o -ø • ½4, respectively. We show results for both dependencies and note that the o -ø • ½0 provides the best agreement with our measurements. It should be noted that inferring the evaporation duct height from radar sea echo is a problem that stresses the modeling of low-grazing-angle backscatter. IntroductionEvaporation ducts result from the rapid change in humidity and temperature that occurs within the surface layer of the atmosphere over bodies of water. The resulting vertical profiles of temperature and humidity change the profile of the index of refraction n and the derivative quantities of radio refractivity N and modified refractivity M so as to form a duct that affects electromagnetic (EM) propagation at frequencies of 1 GHz and above. Evaporation duct refractivity profiles are most often calculated using Monin-Obukhov similarity-theory-based models of Jeske [1971, 1973] surements of the sea surface temperature Ts, air temperature Ta, relative humidity RH, and wind speed U at a reference height above the sea surface. These are commonly referred to as "bulk measurements." The Jeske profile under neutral conditions (T a = Ts) is uniquely defined by the evaporation duct height 3, which is the height at which the refractivity profile changes from downward to upward refracting. The J...

The Coupled Air–Sea Processes and Electromagnetic Ducting Research (CASPER) project aims to better quantify atmospheric effects on the propagation of radar and communication signals in the marine environment. Such effects are associated with vertical gradients of temperature and water vapor in the marine atmospheric surface layer (MASL) and in the capping inversion of the marine atmospheric boundary layer (MABL), as well as the horizontal variations of these vertical gradients. CASPER field measurements emphasized simultaneous characterization of electromagnetic (EM) wave propagation, the propagation environment, and the physical processes that gave rise to the measured refractivity conditions. CASPER modeling efforts utilized state-of-the-art large-eddy simulations (LESs) with a dynamically coupled MASL and phase-resolved ocean surface waves. CASPER-East was the first of two planned field campaigns, conducted in October and November 2015 offshore of Duck, North Carolina. This article highlights the scientific motivations and objectives of CASPER and provides an overview of the CASPER-East field campaign. The CASPER-East sampling strategy enabled us to obtain EM wave propagation loss as well as concurrent environmental refractive conditions along the propagation path. This article highlights the initial results from this sampling strategy showing the range-dependent propagation loss, the atmospheric and upper-oceanic variability along the propagation range, and the MASL thermodynamic profiles measured during CASPER-East.

[1] Estimation of the range-and height-dependent index of refraction over the sea surface facilitates prediction of ducted microwave propagation loss. In this paper, refractivity estimation from radar clutter returns is performed using a Markov state space model for microwave propagation. Specifically, the parabolic approximation for numerical solution of the wave equation is used to formulate the refractivity from clutter (RFC) problem within a nonlinear recursive Bayesian state estimation framework. RFC under this nonlinear state space formulation is more efficient than global fitting of refractivity parameters when the total number of range-varying parameters exceeds the number of basis functions required to represent the height-dependent field at a given range. Moreover, the range-recursive nature of the estimator can be easily adapted to situations where the refractivity modeling changes at discrete ranges, such as at a shoreline. A fast range-recursive solution for obtaining range-varying refractivity is achieved by using sequential importance sampling extensions to state estimation techniques, namely, the forward and Viterbi algorithms. Simulation and real data results from radar clutter collected off Wallops Island, Virginia, are presented which demonstrate the ability of this method to produce propagation loss estimates that compare favorably with ground truth refractivity measurements.

In coastal regions the presence of the marine boundary layer can significantly affect RF propagation. The relatively high specific humidity of the underlying "marine layer" creates elevated trapping layers in the radio refractivity structure. While direct sensing techniques provide good data, they are limited in their temporal and spatial scope. There is a need for assessing the three-dimensional (3-D) time-varying refractivity structure. Recently published results (Gingras et al.[1]) indicate that matched-field processing methods hold promise for remotely sensing the refractive profile structure between an emitter and receive array. This paper is aimed at precisely quantifying the performance one can expect with matched-field processing methods for remote sensing of the refractivity structure using signal strength measurements from a single emitter to an array of radio receivers. The performance is determined via simulation and is evaluated as a function of: 1) the aperture of the receive array; 2) the refractivity profile model; and 3) the objective function used in the optimization. Refractivity profile estimation results are provided for a surface-based duct example, an elevated duct example, and a sequence of time-varying refractivity profiles. The refractivity profiles used were based on radiosonde measurements collected off the coast of southern California.