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A layer of oil on the sea surface reduces the components of ocean wave spectra corresponding to the capillary and gravity-capillary waves leading to significantly reduced radar backscatter and making slicks appear dark in synthetic aperture radar (SAR) images. The ratio of the backscatter between clean and slicked ocean surfaces is known as the ‘damping ratio,’ and has been shown to be sensitive to variations within slicks that correlate with the oil layer’s thickness and fractional water volume. Although the relative thickness relationship is well established and can be used to identify areas of ‘thicker’ oil within a slick, quantifying the thickness from SAR alone remains to be shown. There is considerable uncertainty regarding the potential capability of SAR to quantitatively determine the oil layer thickness for slicks in open water given the dependence on bulk and interfacial oil layer properties and the variation of the properties typical in this setting and for different types of oil. Here, we report the results of a study modeling radar backscatter from slicked and unslicked ocean surfaces based on electromagnetic scattering theory and accounting for oil properties and meteorological conditions. The electromagnetic scattering model is used to evaluate whether the oil thickness can be quantified with reasonable accuracy based upon SAR backscatter intensities alone, and how information about metocean conditions, oil properties and ocean temperature and salinity can be used to calibrate the model to obtain more accurate thickness estimates.The research was carried out at the Jet Propulsion Laboratory, California Institute of Technology, under contract with the National Aeronautics and Space Administration.

The accurate estimation of grid-scale fluxes of water, energy, and carbon requires consideration of subgrid spatial variability in root-zone soil moisture (RZSM). The NASA Airborne Microwave Observatory of Subcanopy and Subsurface (AirMOSS) mission represents the first systematic attempt to repeatedly map high-resolution RZSM fields using airborne remote sensing across a range of biomes. Here, we compare 3-arc-sec (∼100 m) spatial resolution AirMOSS RZSM retrievals from P -band radar acquisitions over nine separate North American study sites with analogous RZSM estimates generated by the Flux-Penn State Integrated Hydrologic Model (Flux-PIHM). The two products demonstrate comparable levels of accuracy when evaluated against ground-based soil moisture products and a significant level of temporal cross correlation. However, relative to the AirMOSS RZSM retrievals, Flux-PIHM RZSM estimates generally demonstrate much lower levels of spatial and temporal variability, and the spatial patterns captured by both products are poorly correlated. Nevertheless, based on a discussion of likely error sources affecting both products, it is argued that the spatial analysis of AirMOSS and Flux-PIHM RZSM fields provides meaningful upper and lower bounds on the potential range of RZSM spatial variability encountered across a range of natural biomes.

This study examines the impact of variation in Root‐Zone Soil Moisture (RZSM), a key component of the Earth's hydrologic cycle and climate system, on regional carbon fluxes across seven North American ecosystems. P‐band Synthetic Aperture Radar‐derived RZSM estimates were incorporated into the Ecosystem Demography (ED2) terrestrial biosphere model through a model‐data blending approach. Analysis shows that the model qualitatively captures inter‐daily and seasonal variability of observed RZSM at seven flux tower sites (r=0.59 ± 0.26 and r= 0.70 ± 0.22 for 0‐10cm and 10‐40cm soil layers, respectively; P

This study examines the potential of using bistatic radar reflections from the Global Navigation Satellite System (GNSS) to classify sea ice types in the Arctic Ocean during the sea ice formation period. For this study, we used data obtained from the United Kingdom (UK) TechDemoSat-1 (TDS-1) satellite mission. The main objective of the TDS-1 mission is to provide L-band radar reflections of the ocean surface in order to infer wind speed through an estimation of the ocean surface roughness. Given the orbit inclination of TDS-1, polar coverage is obtained providing datasets over the Arctic sea ice cover. Recent studies demonstrated the use of TDS-1 data for accurately deriving ocean-ice detection using the shape of the bistatic radar waveforms derived from delay-Doppler maps. We aim to advance this previous research by demonstrating the sensitivity of GNSS bistatic radar signals to sea ice types. The originality of the study presented in this manuscript is the classification of sea ice types, never implemented before with any GNSS-R mission. For this study, we examined the fall period of October 2015 in the Beaufort and Chukchi seas region, when considerable expanses of young ice, first-year ice (FYI), and multi-year ice (MYI) were present. We developed a sea ice multi-step classification approach based on bistatic radar reflections to generate not only an ocean-ice classification but to classify between the three dominant ice types present. The classification was done in multiple steps based on GNSS bistatic radar observations only and includes checks for spatio-temporal consistency with each dominant class. Validation results are based on the comparison of the GNSS classification against SAR-derived sea ice type maps produced at the US National Ice Center. First, we derived classifications of sea ice–open water samples with a success rate of 97%, comparable to previous studies. Next, the sea ice type classification results identified FYI, MYI and young ice with success rates of 70%, 82% and 81%, respectively, indicating a strong sensitivity of the L-band GNSS bistatic radar signals to the different surface scattering properties of these primary ice types. With this manuscript we demonstrate the potential of the GNSS bistatic radar signals to classify ice types during the sea ice formation period. GNSS bistatic radar signals provide unique forward scattered measurements at L-band, potentially on a daily temporal revisit, that can be used to produce enhanced information on sea ice characteristics, such as those currently generated by other sensors. In order to determine the use of GNSS-R measurements on an operational basis, further studies are needed over a year-long period of sea ice growth and melt to determine the full benefit of GNSS for improving and providing complementary information to that generated by both microwave and optical sensors.

Imaging of objects through complex environment is important in several applications, including imaging of hidden objects in obscuring media such as atmospheric and ocean turbulence, rough ocean surfaces, rain, fog, snow, and biological tissues. These media are often randomly varying in space and time, and statistical treatments are necessary to obtain images with useful spatial and temporal resolutions. In recent years, there has been increasing interest in using signal processing and correlation techniques to improve resolutions and to distinguish images from clutter. This paper presents several imaging techniques for objects in the presence of random media. Time-reversal MUSIC (multiple signal classification) imaging has excellent resolution when multiple scattering is small or moderate. Modified beamformer imaging has moderately high resolution even at large multiple scattering. We also include time reversal (TR) and synthetic aperture radar (SAR) imaging for comparison. The technique involves stochastic Green's function and mutual coherence function (MCF), eigenvectors of time-reversal matrix and pseudo spectrum. Numerical examples are given to show the effectiveness of these imaging techniques.

Multiple input-multiple output systems have received considerable attention because of their potential to achieve high channel capacity. This paper presents a study of the effects of a random scattering medium on channel capacity. Formulations are given including stochastic Green's functions and mutual coherence functions. Transmitter and receiver characteristics are included and analytical formulation for eigenvalues and channel capacities are given in terms of the medium scattering characteristics, optical depth, frequency, number of transmitter and receiver elements, transmitting power, and noise spectral power. As an example, we show 500 m link at 60 GHz through rain. The eigenvalues and the channel capacity are calculated in terms of SNR and the rain rate representing the optical depth. It is shown that as the rain rate increases, the correlation of waves at antennas decreases and the capacity increases. However, at high rain rate, the capacity tends to decrease due to the absorption and scattering.

We analyse the problem of the estimation of the angle of arrival in discrete random scattering media. Assuming incidence of a plane wave, we derive the performance of the determination of the angle of arrival in terms of beamwidth, which reflects the ability to resolve the angle of arrival from several directions. The minimum variance beamformer or Capon beamformer is applied. We demonstrate that in random scattering media the signal arriving at the receiving array shows correlation and is modelled as a Gaussian function, and this correlation deteriorates the ability to determine the angle of arrival. A matrix compensation is introduced to improve the performance by correcting the correlation. The main parameter in compensation is the correlation length. We investigate the effect of the correlation length on the angle of arrival.

The time-reversal effects on super-resolution in random scattering media are analysed using numerical finite-difference time-domain (FDTD) simulations. The analytical solutions and results have been presented previously in the literature, which provide confirmation of spot-size reduction and also explanations of the shower curtain effects and backscattering enhancement. However, the analytical solutions are based on several approximations. Thus, validation of the analytical results against realistic scattering events is necessary. Two-dimensional FDTD Monte Carlo simulations have been employed for this investigation to simulate wave propagation and scattering in a random medium. The scattering environments are created by randomly locating cylindrical rods in the background medium. The simulation process involves a point source emitting a Gaussian pulse wave that propagates through the scattering medium, gets time-reversed, and then back-propagated into the same scattering medium. The focusing behaviours i...

Imaging through discrete random media is an important problem in several applications such as medicine, remote sensing, and security. Discrete random media create scattering which deteriorates the quality of the image and there have been several efforts to mitigate the problem. We propose an array processing method called coherence tomography array (CTA) whose algorithm is derived from that of optical coherence tomography. We use the Monte Carlo method to simulate the imaging scenarios in random scattering media. The results show that CTA can be used to alleviate the clutter effects from discrete random scatterers.

A general formulation of a theory of imaging through random obscuring layers is described. Previously we presented a theory for the temporal behavior of a short pulse scattered from a random medium and from a point target. In this paper, we generalize our study to include the imaging of objects of finite size and the actual imaging pattern at the receiver. This involves the study of two-frequency fourth order moments. Numerical examples are given to illustrate several important features, including the optical depth, backscattering enhancement, shower curtain effects, aperture size, bandwidth and target size.

This paper presents a theory of imaging objects behind layers of scattering media. The transmitter is a focused array or an aperture emitting a short pulse. The scattered pulse is received by a focused array or aperture. The received signal consists of two components: the pulse scattered from a random medium and from the target, and these two components can be distinguished by the use of ultra wide band (UWB) pulse. The second moment of the received signal includes the fourth-order moments of stochastic Green's functions, which are reduced to the second moments by the use of the circular complex Gaussian assumption, and of the generalized two-frequency mutual coherence function. This imaging theory is a generalization of optical coherence tomography (OCT), SAR and confocal imaging. It clarifies the relationships among resolution, coherence length, shower curtain effects and backscattering enhancement.

Most electromagnetic problems deal with media with unit permeability. However, recent interest in metamaterials necessitated studies of wave characteristics in media with arbitrary permittivity and permeability whose real parts can be positive or negative. This paper presents analysis of wave characteristics on semiinfinite metamaterials. Waves are excited by electric or magnetic line sources, and the problem is separated into the p (TM) and the s (TE) polarization, showing symmetries. The Fourier spectra of the reflection and transmission coefficients are examined and the poles, branch points, and zeros are shown in the real /spl mu/-real /spl epsi/ diagram. We clarify the location of poles in proper and improper Riemann Surfaces, and the excitation of forward and backward surface waves, forward and backward Lateral waves, and Zenneck waves, and the relations between Brewster's angle and Sommerfeld poles. We include the behaviors of the backward surface waves and the temporal backward Lateral waves.

This paper presents a theory of the radar cross section (RCS) of objects in multiple scattering random media. The general formulation includes the fourthorder moments including the correlation between the forward and the backward waves. The fourth moments are reduced to the second-order moments by using the circular complex Gaussian assumption. The stochastic Green’s functions are expressed in parabolic approximation, and the objects are assumed to be large in terms of wavelength; therefore, Kirchhoff approximations are applicable. This theory includes the backscattering enhancement and the shower curtain effects, which are not normally considered in conventional theory. Numerical examples of a conducting object in a random medium characterized by the Gaussian and Henyey–Greenstein phase functions are shown to highlight the difference between the multiple scattering RCS and the conventional RCS in terms of optical depth, medium location and angular dependence. It shows the enhanced backscattering due to multiple scattering and the increased RCS if a random medium is closer to the transmitter.

The problem of polarized light propagating through scattering media can be explained using the vector radiative transfer equation. This equation is an integro-differential equation and is well-known to be unsolvable analytically. One of the approximate solutions is discrete ordinates method which is based on the discretization of the Stokes parameters and the Mueller matrix. Although it produces accurate results, it requires a lot of computational resources. In addition, there are limitations on the calculation for angles that are very close to the optical axis. The solutions at these angles are necessary for some applications such as atmospheric imaging. First-order scattering approximation has been applied to mitigate the computational resource situation. It can also be used to calculate the solution at the angles that are very close to optical axis. However, it lacks information about the cross-polarization and it is inaccurate when light encounters more scattering events. Second-order scattering approximation provides more accurate solutions and offers some information about cross-polarization. We develop the first-order and second-order scattering approximations and their solutions for the pulse wave case. We investigate the second-order approximation solutions and compare them to the solution from the complete vector radiative transfer equation in several cases.

The passage of a photon density wave through random media has been investigated extensively for medical imaging based on the diffusion approximation. In this paper, the photon density wave is studied based on the exact time-dependent vector radiative transfer theory. Both continuous and pulse photon density waves are analysed in a plane parallel medium using Mie scattering and the discrete ordinates method. The photon density wave shows superior properties over regular waves in several aspects. It has a narrower angular spectrum and maintains the original pulse shape. It also preserves the degree of polarization and increases the cross-polarization discrimination. These properties of a photon density wave suggest its potential for improving imaging. Thus, we apply the photon density wave to an imaging problem and show that it improves the quality of the images compared to other conventional imaging techniques.

The NASA Earth Observing System Simulators Suite (NEOS3) is a modular framework of forward simulations tools for remote sensing of Earth's Atmosphere from space. It was initiated as the Instrument Simulator Suite for Atmospheric Remote Sensing (ISSARS) under the NASA Advanced Information Systems Technology (AIST) program of the Earth Science Technology Office (ESTO) to enable science users to perform simulations based on advanced atmospheric and simple land surface models, and to rapidly integrate in a broad framework any experimental or innovative tools that they may have developed in this context. The name was changed to NEOS3 when the project was expanded to include more advanced modeling tools for the surface contributions, accounting for scattering and emission properties of layered surface (e.g., soil moisture, vegetation, snow and ice, subsurface layers). NEOS3 relies on a web-based graphic user interface, and a three-stage processing strategy to generate simulated measurements. The user has full control over a wide range of customizations both in terms of a priori assumptions and in terms of specific solvers or models used to calculate the measured signals.This presentation will demonstrate the general architecture, the configuration procedures and illustrate some sample products and the fundamental interface requirements for modules candidate for integration.

Imaging and detection of objects in the presence of rough surfaces and random media are important current problems with applications in object detection near rough ocean surfaces and terrain, and remote sensing in geophysical and biological media. It has also been important to incorporate signal processing techniques to space-time imaging. This paper presents applications of several signal processing techniques to imaging in complex environments, including Time-Reversal MUSIC imaging in random media. Also discussed are the effects of multiple scattering on several other imaging techniques including Time-Reversal, Modified Beamformer, and SAR. In particular, we discuss the imaging of objects located near rough surfaces.

In recent years there has been increasing interest in the use of polarization for imaging objects in a cluttered environment. Examples are optical imaging through clouds, optical detection of objects in a biological medium, and microwave detection of objects in clutter. We extend previous studies of continuous-wave scattering to pulse-polarization scattering in discrete scatterers. We solve the time-dependent vector radiative transfer equation for a plane-parallel medium by using Mie scattering and the discrete ordinates method. The time-dependent degree of polarization and cross-polarization discrimination are calculated and verify the advantages of circular over linear polarization in maintaining greater copolarized components rather than cross-polarized components.

[1] In this paper, we present analytical theories of the first and second moments of the time-reversed pulse which are obtained by the second- and the fourth-order moments of stochastic Green's functions in random media. The theories are based on the use of parabolic approximations, two-frequency mutual coherence function, and the circular complex Gaussian assumptions. Several effects are discussed including the superresolution, the coherence length, backscattering enhancement, the dependence on the optical depth, the shower curtain effect, and the bandwidth.

Wireless communication in unknown and cluttered environments is an important problem which has several practical applications such as communication in urban areas and disaster areas. This paper presents a method to optimize communication efficiency in such environments. The method applies to communication between a transmitting array and receiving array where the transmitting array sends out a 'probe' signal and, at the receiving array, the transfer matrix can be constructed. From this measurement, we perform time-reversal and eigen analysis. The highest eigen value is the best possible transmission efficiency and its corresponding eigen vector represents the transmitting excitation at the transmitting elements to achieve maximum efficiency. The nature of this method makes it possible to operate and optimize in unknown, random, and cluttered environments. Here, we present the theory of time-reversal communication, show relevant numerical examples, and illustrate the experimental verification.

This paper presents an electromagnetic model based on multi-layer media. This model includes multiple reflections within each layer, and it has the flexibility to include more complicated structures. Simulations of frequency response and pulse wave through this multi-layer structure are presented. This model provides a tool to estimate the responses at different frequencies and configurations which is instrumental to imaging and detection of objects

The thickness of Arctic sea ice plays a critical role in Earth's climate and ocean circulation. An accurate measurement of this parameter on synoptic scales at regular intervals would enable characterization of this important component for the understanding of ocean circulation and the global heat balance. Presented in this paper is a low frequency VHF interferometer technique and associated radar instrument design to measure sea ice thickness based on the use of backscatter correlation functions. The sea ice medium is represented as a multi-layered medium consisting of snow, sea-ice and sea water, with the interfaces between layers characterized as rough surfaces. This technique utilizes the correlation of two radar waves of different frequencies and incident and observation angles, scattered from the sea ice medium. The correlation functions relate information about the sea ice thickness. Inversion techniques such as the genetic algorithm, gradient descent, and least square methods, are used to derive sea ice thickness from the phase information related by the correlation functions. The radar instrument is designed to be implemented on a spacecraft and the initial test-bed will be on a Twin Otter aircraft. Radar system and instrument design and development parameters as well as some measurement requirements are reviewed. The ability to obtain reliable phase information for successful ice thickness retrieval for various thickness and surface interface geometries is examined.

There is an increasing interest in free space optics (FSO) communication systems among data service providers. The cost of installing a new fiber network in an urban environment is often very expensive, and a less expensive method is needed. A high-speed data link, for example, can be designed using either optical or millimeter-wave (MMW) point-to-point communication systems. The optical system is often the preferred method because of its simplicity and security. The data rate for short distance FSO systems in an ideal condition can exceed one Gbit/sec. However, both MMW and optical links are susceptible to adverse weather conditions. The traditional method to estimate the effects of an atmospheric channel is to calculate the attenuation characteristics based on the size distribution and concentration of particles along the signal path length. From the signal attenuation rate, the bit-error rate is usually estimated. This approach, however, does not consider the propagation characteristics of modulated signals. We give a numerical method to calculate the waveform of an intensity modulated optical signal through a layer of fog and cloud. Our approach takes into account the multiple scattering effects and reveals a substantial amount of waveform distortion.

We have studied the polarization characteristics of light scattered from randomly distributed spherical particles using the 4x4 Mueller matrix. The experimental system consists of a Helium-Neon laser, polarizers (vertical, horizontal, 45-degree linear, left-hand circular) and six analyzers (vertical, horizontal, 45-degree linear, 135-degree linear, right-hand circular, left-hand circular). If the six polarized states of the scattered light for a given incident polarization are measured with analyzers, we can calculate the Stokes vector. By repeating this measurement for four independent incident polarizations, we can obtain the complete Mueller matrix. Random media consist of spherical particles of different concentrations suspended in water. The numerical study is based on the complete solution of the radiative transfer equation. Using the discrete ordinate method and matrix solver, we obtain the Stokes vector for a given incident polarization. By calculating Stokes vector for four independent polarizations, we can obtain a full Mueller matrix. The experimental results are compared with the numerical analysis.

Imaging through random media is an important problem with many applications including optical remote sensing and bio-optics. As the optical depth gets larger, the imaging resolution and contrast deteriorates because of the effect of scattering. In this paper, we present the solution to the vector radiative transfer equation (VRTE) and its application to the optical imaging problem. Since the incoherent component created by the scattering in random media is responsible for the deterioration of the quality of images, several techniques are proposed to improve the imaging by reducing the incoherent component. The Off-Axis Intensity Subtraction (OAIS) and Cross-Polarization Intensity Subtraction (CPIS) imaging techniques are based on the fact that off-axis and cross polarization contains most of the incoherent component. Photon Density Waves (PDW) is a frequency-domain method which exhibits less effect of multiple scattering from the random media. We investigate the techniques mentioned above using numerical solution of VRTE and show the effectiveness, the limitations and the conditions of these techniques. Because we consider the polarized pulse wave case, we also discuss the time-domain behavior and the application of time-gating to the imaging problem. The time-gating method is investigated in both position and duration. Since in practice an array of detectors are often used, we also include the effect of Field Of View of a detector (pixel FOV) in our calculations. We quantitatively measure the performance of imaging techniques by contrast. Also, we apply these techniques to numerical simulations of cross images and show the improvement of the quality of the images.© (2002) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

Communication through turbulence and particulate matters such as rain are seriously affected by multiple scattering. We present a study on multiple‐input‐multiple‐output system in random medium and its channel capacity making use of the stochastic Green’s functions and the mutual coherence function (MCF). The channel matrix and the eigenvalues are given explicitly in terms of the medium characteristics, and the channel capacity is given in terms of signal‐to‐noise ratios, eigenvalues, and the antenna gain characteristics. MCF is given in terms of the power spectrum for turbulence and the optical depth, phase function, and albedo for particulate matters. Next, we consider imaging through random medium such as biological media. We present several space‐time array signal processing imaging techniques which include time‐reverse imaging, time‐reverse multiple signal classification, Capon minimum variance, modified beam former, and SAR. We discuss the advantages and the disadvantages of these techniques with numerical examples. The effects of array sizes, Fresnel size, bandwidth, the distance, and the medium characteristics on the transverse and longitudinal resolutions are clarified. This study is aimed at combining the propagation and scattering and the array signal processing for communication and imaging in a random complex environment such as turbulence and biological media.

Fog is a highly dispersive medium at optical wavelengths, and the received pulse waveform may suffer significant distortion. Thus it is desirable to have the impulse response of the propagation channel to recover data transmitted through fog. The fog particle density and the particle size distribution both strongly influence the channel impulse response, yet it is difficult to estimate these parameters. We present a method using a dual-wavelength free-space optical system for estimating the average particle diameter and the particle number density and for approximating the particle distribution function. These parameters serve as inputs to estimate the atmospheric channel impulse response using simulation based on the modified vector radiative transfer theory. The estimated channel response is used to design a minimum mean-square-error equalization filter to improve the bit error rate by correcting distortion in the received signal waveform due to intersymbol interference and additive white Gaussian noise.

Feature Issue on Optical Wireless Communications (OWC) The modified vector radiative transfer equation is solved in the frequency domain to study the frequency response of the propagation channel. In the time domain, the impulse response is obtained by taking the inverse Fourier transform of the frequency response. The time-domain analysis investigates the effects of the receiver's field of view on reducing the bit error rate when there is intersymbol interference caused by the temporal spread of the received signal.