Microwave Scatter Research Articles

Microwave Anechoic Chamber Measurement and Scatter Characteristics Analysis of Typical Wetland Vegetation in South China

Microwave Anechoic Chamber Measurement and Scatter Characteristics Analysis of Typical Wetland Vegetation in South China

Utilization efficiency of microwave energy for granular food in continuous drying: From propagation properties to technology parameters

To elucidate the utilization efficiency of microwave energy (UEME) of granular food, germinated brown rice (GBR) as a representational material, in a continuous microwave dryer, the propagation of microwave energy inside drying cavity and the effects of technology parameters on the energy consumption of GBR material layer were investigated by using numerical simulation and bench experiments. Results indicate that the transmission loss of microwave scatter from the waveguide ports decline with the increase of thickness of grain layer in drying cavity. The total absorption of microwave energy is achieved in the thickness of material processed exceeding critical depth of microwave penetration to reduce the scatter loss of microwave transmission. In microwave cavity, the dissipation of microwave energy inside material processed alters the modes and frequency of microwave propagation and resonance, and continuous movement and ventilation process may promote UEME due to the improvement of drying uniformity of GBR. High UEME may be achieved at the temperature of GBR material layer in range of 100 ± 5 °C till final moisture content of 14.5% (w.b.). The optimal technology parameters of microwave drying for GBR is obtained as microwave intensity of 2 W/g, ventilation velocity of 1.0–1.5 m/s, drying duration for per drying pass of 6 min, and the thickness of GBR layer of 8 mm to achieve high UEME. The research results provide significant insights to evaluate the electric field distribution and design industrial microwave dryer with high utilization efficiency of microwave energy.

Application of Markov Random Field on Microwave Near-Field Imaging of Breast Tumor

This paper solved an inverse scattering problem of near field under some conditions and presented a novel microwave near-field imaging method of breast tissues with tumors, which is based on the contrast of dielectric properties between normal breast tissues and tumors. We used microwave scatter- sounding method to detect the breast and obtained the reconstruction projection data. Then modeled the dielectric properties distribution of breast tissues with Markov Random Field (MRF) method. With the characteristics of radial distribution of the data, we established the relationship between dielectric properties distribution and detected data. Using Maximum a Posteriori (MAP) estimation, we obtained an optimization problem and solved it. The simulation result shows that the method is effective for imaging.

Polar Format Imaging Algorithm With Wave-Front Curvature Phase Error Compensation for Airborne DLSLA Three-Dimensional SAR

Airborne downward-looking sparse linear array 3-D synthetic aperture radar operates nadir observation and obtains the 3-D microwave scatter information of the observed scene. A polar format algorithm (PFA) with space-variant wave-front curvature phase error compensation is presented. A 3-D image in polar coordinate can be obtained with the proposed PFA, and a 3-D image in Cartesian coordinate can be obtained with interpolation. The proposed PFA possesses the advantages of high precision, low memory requirement, and low computational complexity. The focus performance of the proposed PFA is validated by 3-D distributed scene simulation with an airborne X-band digital elevation model and a P-band circular SAR image of the same area as simulation scene input.

Evaluation of passive microwave snow water equivalent retrievals across the boreal forest/tundra transition of western Canada

Composite patterns of monthly averaged (1978–2002) satellite passive microwave derived snow water equivalent (SWE) data produced using the Meteorological Service of Canada land cover sensitive algorithm suite contain an interannually consistent and well-defined zone of high SWE retrievals (> 100 mm) across the northern boreal forest of western Canada. Consistently lower SWE retrievals are present across both the comparatively dense boreal forest to the south, and open tundra to the north. Because of the sparse conventional observing network across this region, a dedicated field sampling campaign was conducted during the 2003/2004 winter season to measure snow properties across these landscape zones in northern Manitoba, Canada. Using road and helicopter access, snow cover measurements were made along an approximately 500 km transect between the communities of Thompson (boreal forest), Gillam (sparse northern boreal forest), and Churchill (open tundra) during late November 2003, and early March 2004. The November 2003 snow survey revealed good agreement between Special Sensor Microwave/Imager (SSM/I) derived SWE retrievals and in situ measurements across the gradient of increasing SWE between Thompson and Gillam, and the well defined zone of high SWE values to the north and east of Gillam. Further to the north, SSM/I derived SWE retrievals over the boreal ecotone and open tundra were consistently lower than the in situ measurements. Results of the March survey (at which point mean snow depths had increased from approximately 30–60 cm) showed an increase in absolute SWE differences between the in situ measurements and passive microwave estimates, but relative agreement between the datasets remained strong. The same SWE gradient across the boreal forest was again captured by both datasets, although tundra retrievals remained consistently low. These findings, along with consideration of snowpack stratigraphy, density, and the potential influence of tundra lakes and ponds on microwave emission and scatter, suggest that development of a tundra-specific SWE retrieval algorithm is necessary. From a scaling perspective, a large range of SWE values were measured on the ground within each satellite footprint, but a comparison of frequency histograms showed that a high percentage of satellite retrievals (November: 93%; March: 63%) fell within ± 20 mm of the median ground measurement.

On the Spatial Distribution of Cloud Particles

Recent studies have led to the statistical characterization of the spatial (temporal) distributions of cloud (precipitation) particles as a doubly stochastic Poisson process. This paper arrives at a similar conclusion (larger-than-Poissonian variance) via the more fundamental route of statistical physics and significantly extends previous findings in several ways. The focus is on the stochastic structure in the spatial distribution of cloud particles. A new approach for exploring the stochastic structure of clouds is proposed using a direct relation between number density variance and the pair correlation function. In addition, novel counting diagrams, particularly useful for analyzing counts at low data rates, demonstrate droplet clustering and striking deviations from Poisson randomness on small (centimeter) scales. These findings are shown to agree with pair correlation functions calculated for droplet counts obtained from an aircraft-mounted cloud probe. Time series of the arrival of each droplet are used to bin the data evenly so as to avoid corruption of the statistics through the operations of multiplication and division. Furthermore, it is shown that statistically homogeneous series of particle counts exhibit super-Poissonian variance. Since it is not always practical or feasible to obtain such direct measurements, the possibility of studying cloud texture using a revival of the idea of coherent microwave scatter from cloud droplets is discussed, including a more complete interpretation of Bragg scatter that seems to explain some recent observations in clouds. Finally, the appearance of clustering and the subsequent geometric distribution of droplet counts are interpreted using basic considerations of turbulence.

Saturn's rings: Particle size distributions for thin layer models

The small physical thickness of Saturn's rings requires that radio occultation observations be interpreted using scattering models with limited amounts of multiple scatter. A new model in which the possible order of near-forward scatter is strictly limited allows for the small physical thickness, and can be used to relate Voyager 1 observations of 3.6-and 13-cm wavelength microwave scatter from Saturn's rings to the ring particle size distribution function n( a), for particles with radius 0.001 ≤ a ≤ 20 m. This limited-scatter model yields solutions for particle size distribution functions for eight regions in Saturn's rings, which exhibit approximately inverse-cubic power-law behavior, with large-size cutoffs in particle radius ranging from about 5 m in ring C to about 10 m in parts of ring A. The power-law index is about 3.1 in ring C, about 2.8 in the Cassini division, and increases systematically with radial location in ring A from 2.7 at 2.10 R s to slightly more than 3.0 at 2.24 R s. Corresponding mass densities are 32–43 kg/m 2 in ring C, 188 kg/m 2 in the Cassini division, and 244–344 kg/m 2 in ring A, under the assumption that the material density of the particles is 0.9 g/cm 3. These values are a factor of 1 to 2 lower than first-order mass loading estimates derived from resonance phenomena. In view of the uncertainties in the measurements and in the linear density wave model, and the strong arguments for icy particles with specific gravity not greater than about 1, we interpret this discrepancy as being indicative of possible differences in the regions studied, or systematic errors in the interpretation of the scattering results, the density wave phenomena, or some combination of the above.

The Effects of the Variations In Sea Surface Temperature and Atmospheric Stability in the Estimation of Average Wind Speed by SEASAT-SASS

The average wind speeds from the scatterometer (SASS) on the ocean observing satellite SEASAT are found to be generally higher than the average wind speeds from ship reports. In this study, two factors, sea surface temperature and atmospheric stability, are identified which affect microwave scatter and, therefore, wave development. The problem of relating satellite observations to a fictitious quantity, such as the neutral wind, that has to be derived from in situ observations with models is examined. The study also demonstrates the dependence of SASS winds on sea surface temperature at low wind speeds, possibly due to temperature-dependent factors, such as water viscosity, which affect wave development.

Thickness of Saturn's Rings Inferred from Voyager 1 Observations of Microwave Scatter

Earth-based telescopic observations indicate that Saturn's rings are about 1 kilometer thick, while spacecraft measurements and theoretical considerations give an upper bound of about 100 meters. Analysis of a shielding effect present in radio occultation provides a sensitive new measure of the ring thickness. On the basis of this effect, Voyager 1 microwave measurements of near-forward scatter imply a thickness ranging from less than 10 meters in ring C to about 20 and 50 meters in the Cassini division and ring A, respectively. Monolayer models do not fit the observations in the latter two regions. The discrepancy between the Earth-based and spacecraft measurements may be due to warps in the ring plane or effects of tenuous material outside the primary ring system.

Detection of rainfall rates utilizing spaceborne microwave radiometers

Over most of the microwave spectrum, raindrops both absorb and scatter radiation producing large changes in brightness temperatures relative to clear or cloudy conditions. Since the structure of rain varies substantially for different rain rates and climatological backgrounds, the raindrop size distribution, the rain-layer thickness and the ice clouds above the rain layer are all important inputs to the model computations. The subsequent modeling involves applying the Mie theory to derive the absorption and scattering effects and the radiative transfer computations to derive the brightness temperature. The radiative transfer calculation is based upon a variational iterative approach which takes account of the multiple scattering effect of the rain layer. Results over both ocean and land backgrounds are demonstrated. It is shown that over ocean background, which is “cold” in the microwave region, lower frequencies are sufficiently sensitive to rain conditions. Over land background, higher frequencies have to be utilized in order to obtain the sensitivity to rain rates. It is also demonstrated that by using discrimination tests of the radiometric data, the rain/no rain decision can be made and the rainfall rate can be retrieved from a statistical inversion technique. The shortcomings of this technique are: (1) the assumption of a homogeneous field of view at different wavelengths can be erroneous, (2) the actual physical structure of the rain layer may be significantly different from the one used in the climatological approach, and (3) the additional uncertainty which may be introduced because of the limitations of the radiative transfer algorithm.

Ocean surface height‐slope probability density function from SEASAT altimeter echo

This paper describes new methods for the interpretation of microwave scatter from the sea. Roughsurface scattering theory has led to an integral equation for the echo voltage in terms of the joint heightslope probability density function (pdf). We have developed methods for the inversion of this equation that do not require the assumption of a model for either the ocean surface or the transmitted pulse. In addition they are far more efficient than traditional grid‐search methods for model fitting. We have applied our methods to SEASAT data taken over Hurricane Fico. Statistical data analysis was performed to give the data covariance matrix and the correlation coefficient between successive waveforms and to trace the propagation of error through the inversion process to give statistical uncertainties in the derived parameters. The usual assumption of Rayleigh statistics is shown to be violated by the data, since the number of degrees of freedom increases linearly with power, independent of sea state; we conclude that this is an instrumental effect. We find that the waveforms are significantly correlated over distances of several kilometers at high sea states and suggest coherence of long ocean waves over these distances as the cause. We obtained waveheight higher‐order parameters by least squares fitting of a Gram‐Charlier model for probability densities to the calculated values. For averages over 160 km of sea, we obtain a mean surface height bias correction, significant waveheight, and height skewness parameter with standard deviations of 4, 0.7, and 15%. In addition to this height bias correction easily removed from the data, we identify another sea‐state‐dependent height bias that can exceed 50 cm. That this exists in the data is proof that one must employ the joint height‐slope pdf in the scattering model, and not merely the height pdf as conventionally used.

A comparative study of microwave radiometer observations over snowfields with radiative transfer model calculations

The increasing demand for water throughout the world imposes a challenging problem for water resources managers. Since the water stored in snowpacks represents an important source of the water supply, a system which monitors and inventories the water equivalent of snow should clearly improve the water resources estimate. Recent results indicate that spaceborne microwave radiometry has the potential for inferring the snow depth and water equivalent information over large snow-covered areas. In order to assess this potential for determining the water equivalent of a snowpack, it is necessary to understand the microwave emission and scatter behavior of the snow at various wavelengths. The emitted microwave radiation is dependent on the physical temperature, crystal size, and density. The basic relationship between the properties of the snowpack and the emitted radiation may be derived by using the radiative transfer approach. Truck-mounted microwave instrumentation was used to study the microwave characteristics of the snowpack in the Colorado Rocky Mountain region in the vicinity of Fraser, Colorado during the winter of 1978. The spectral signatures of 5.0, 10.7, 18, and 37 GHz radiometers with dual polarization were used. These data compared favorably with calculated results based on recent microscopic scattering models.

Snow parameter determination by multichannel microwave radiometry

A long-term observational program on the microwave scatter and emission behavior of snow began in 1977 at a high-altitude Alpine test site. The brightness temperatures at 4.9, 10.5, 21, 36, and 94 GHz measured at different incidence and polarization angles during the first season are analyzed with the aid of correlation, factorial, and cluster algorithms. The structure mathematically found within the data is compared with classical parameters of the snow cover. Snow state changed from a high winter state to a late spring state during our measurements. At least three different snow qualities and two grades of moisture for the uppermost 10 cm of the snow layer can clearly be distinguished with a high degree of accuracy. The information content of our measurements does not substantially degrade by reducing our data to data as delivered by the NIMBUS-5 and as expected of the NIMBUS-G satellites. Recommendations for optimum frequencies for the remote sensing of snow are given.

Microwave scatter and sea state estimation: Two-scale ocean wave models

The efficient estimation of ocean wave-structure parameters with a remote, narrow-beam, pulsed, microwave radar at intermediate incidence angles is discussed. The sea surface is described as the sum of random small- and large-scale structures (waves), the latter the sum of a sinusoid and a random field. It is shown that the small-scale structure is responsible for scattering and that the scatter depends parametrically on the large-scale structure. For the estimation problem it is assumed, reasonably, that the received signal is normally distributed: a relatively simple processor which will efficiently estimate parameters of the sinusoidal structure is illustrated and its performance discussed. A brief comparison is made with a normal incidence system with which the variance of the large-scale random roughness can be estimated.