Search

A study of an ultrawideband frequency-modulated continuous-wave radar with an extended frequency sweep from 0.5 to 8 GHz is presented. It has been applied to through-the-wall human detection. This work presents the modeling of wall attenuation followed by real measurements. The radar system is presented, and trials of human being tracking are shown. This radar will enable large stand-off distance capabilities and "in-depth" building detection. [ABSTRACT FROM AUTHOR]

In this paper, an investigation of the potential of rapid refractivity retrieval is presented. The retrieval technique utilizes radar phase measurements of ground clutter to derive near-surface refractivity, which has been commonly used as a proxy for humidity, given its close relation to vapor pressure. Surface humidity is an important meteorological parameter and has been known to play an important role in convective initiation. In this paper, the refractivity retrieval technique is exploited by using smaller numbers of samples for phase calculation, which is a fundamental process in refractivity retrieval. The impetus for this paper is to explore the possibility of rapid refractivity retrieval by exploiting the rapid beam-steering capability of a phased-array radar. Using the National Weather Radar Testbed in Norman, OK, a 64-pulse per radial raw-data set was collected for conventional refractivity processing. Then, subsets of the 64 samples were extracted to emulate shorter dwell periods and the corresponding more rapid experiments. The test cases that were considered are 2, 4, 8, 16, and 32 samples. Refractivity fields retrieved using smaller numbers of samples are compared against the reference field, which was obtained using the entire 64-sample data set. It will be shown that, statistically, significant refractivity fields can be obtained from as short as a two-sample dwell. [ABSTRACT FROM AUTHOR]

This paper reports on the retrieval of soil moisture from dual-polarized L-band (1.6 GHz) radar observations acquired at view angles of 15°, 35°, and 55°, which were collected during a field campaign covering a corn growth cycle in 2002. The applied soil moisture retrieval algorithm includes a surface roughness and vegetation correction and could potentially be implemented as an operational global soil moisture retrieval algorithm. The surface roughness parameterization is obtained through inversion of the Integral Equation Method (IEM) from dual-polarized (HH and VV) radar observations acquired under nearly bare soil conditions. The vegetation correction is based on the relationship found between the ratio of modeled bare soil scattering contribution and observed backscatter coefficient (σsoil/σobs) and vegetation water content (W). Validation of the retrieval algorithm against ground measurements shows that the top 5-cm soil moisture can be estimated with an accuracy between 0.033 and 0.064 cm³ · cm-3, depending on the view angle and polarization. [ABSTRACT FROM AUTHOR]

Oversampling weather radar signals in range and then whitening these signals has been shown to improve the accuracy of spectral moments. For dual-polarized radar, the polarimetric variables depend upon information gleaned from the cross correlation of the different received signals. Theoretical improvements to the polarimetric variables have been provided to date, but experimental evidence of improvements through whitening has been limited. This paper provides an analysis of the effects of whitening on the estimated cross correlation along with experimental results of whitening applied to polarimetric variables. Different whitening transformations based solely on covariance matrix inversions will be shown to affect the copolar correlation of the whitened data. A Hermitian symmetric whitening transformation will be shown to produce better estimates of polarimetric variables obtained from whitened data than the original whitening transformation defined for use with range oversampling. [ABSTRACT FROM AUTHOR]

Morphodynamic processes in coastal areas are affected by tidal currents and sea state. The continuous observation of near coastal areas is important in order to monitor dangerous current-regime and bathymetry changes. Therefore, there is an urgent need for remote sensing techniques delivering the important hydrographic parameters with a high spatial resolution. Dispersive Surface Classificator (DiSC) is a newly developed method based on the analysis of nautical X-band radar image sequences of sea surface waves to determine spatial maps of hydrographic parameters, e.g., spatial maps of the bathymetry and the ocean current field. The method DiSC is described and is illustrated by the presentation of results based on a dataset acquired with a ground-based X-band radar installation mounted on the Island of Sylt in the German Bight. The calculated bathymetric maps are verified by multibeam echo sounder observations. [ABSTRACT FROM AUTHOR]

This paper presents the results of a study designed to classify weather radar clutter echoes obtained from ground-based dual-polarization weather radar systems. The clutter signals are due to ground clutter, sea clutter, and anomalous propagation echoes, which represent sources of error in quantitative radar rainfall estimation. Fuzzy and Bayes classifiers are evaluated as an alternative approach to traditional polarimetric-based methods. Both systems were trained and validated by using C-band dual-polarization radar measurements, and a novel technique is proposed to calculate the texture function to mitigate against the edge effects at the boundaries of precipitation regions. A methodology is presented to extract the membership functions and conditional probability density functions to train the classifiers. The critical success index indicates that the Bayes classifier has, on average, a slightly better performance than the fuzzy classifiers. However, when optimal weighting was applied, the fuzzy classifier gave one of the best performances. The classifiers are sufficiently robust to be used when only single-polarization radar measurements are available. [ABSTRACT FROM AUTHOR]