The problem of coherent reflecton of an acoustic plane wave from a random seabed consisting of a randomly inhomogeneous sediment layer overlying a uniform elastic sea floor is considered in this analysis. The random perturbation in the sediment layer is attributable to the sound-speed variations, resulting in volume scattering due to medium inhomogenieties. An approach based upon perturbation theory, combining with a derived Green's function for a slab bounded above and below respectively by a fluid and an elastic half space ,is employed to obtain an analytic solution for the coherent field in the sediment layer. A linear system is then constructed to facilitate the analysis of the coherent reflection field. The results of the coherent reflection coefficient for various sediment randomness, frequency , sediment thickness, and sea floor elasticity have been numerically generated and analyzed. It was found that the higher/larger size of randomness , frequency, thickness, and shear-wave speed, the lower the coherent reflection. Physical interpretation for the characteristics of various results were provided.

Spaceborne scatterometers have measured the normalized radar cross section (RCS) of the earth's surface for several decades. Two frequencies, C- and Ku-band, have been used in designing scatterometers, such as with the Ku-band NASA Scatterometer (NSCAT) and the C-band Advanced Scatterometer (ASCAT). The scatterometer data record between C- and Ku-band has been disjoint for several decades due to the difficulties in cross calibration of sensors that operate at different frequencies and incidence angles. A model for volume scattering over the Amazon rainforest canopy that includes both the incidence angle and frequency dependence is developed to overcome this challenge in cross calibration. Several models exist for the σ0 incidence angle dependence, however, none of them are based on backscatter physics. This thesis develops a volume scattering model from a simple EM scattering model for cultural vegetation canopies and applies it to the volume scattering of the Amazon rainforest. It is shown that this model has lower variance than previously used models for the incidence angle dependence of σ0, and also enables normalization of σ0 with respect to the incidence angle. In addition, the frequency dependence of σ0 is discovered to be quite sensitive at Ku-band due to the distribution of leaf sizes in the Amazon rainforest. This may limit the accuracy of the model of the frequency dependence of σ0. Although the proposed frequency dependence model may be limited for cross calibrating between C- and Ku-band, it provides the groundwork for future studies.

Terahertz (THz) spectroscopy can potentially be used to probe and characterize inhomogeneous materials, however spectroscopic identification of such materials from spectral features of diffuse returns is a relatively underdeveloped area of study. In this thesis, diffuse THz scattering from granular media is modeled by applying radiative transfer (RT) theory for the first time in THz sensing. Both classical RT theory and dense media radiative transfer (DMRT) theory based on the quasi-crystalline approximation (QCA) are used to calculate diffuse scattered intensity. The numerical solutions of the vector radiative transfer equations (VRTE) were coded and calculated in MATLAB. The diffuse scattered field from compressed Polyethylene (PE) pellets containing steel spheres was measured in both transmission and reflection using a THz time domain spectroscopy (THz-TDS) system. Measurement results showed energy redistribution by granular media due to volume scattering as well as angle dependent spectral features due to Mie scattering. The RT model was validated by successfully reproducing qualitative features observed in experimental results. Diffuse intensity from granular media containing Teflon, lactose sugar, and C4 explosive was then calculated using the RT models. Simulation results showed the amplitude of diffuse intensity is affected by factors such as grain size, fractional volume of grains, thickness of scattering layer, and scattering angles. Spectral features were also observed in the diffuse intensity spectra from media containing grains with THz spectral signatures. The simulation results suggest the possibility of identifying materials from diffuse intensity spectra.

Remote sensing is the collection of information about an object from a distance without physically being in contact with it. The type of remote sensing of interest here is in the form of digital images of water bodies acquired by satellite. The advantage over traditional sampling techniques is that data can be gathered quickly over large ranges, and be available for immediate analysis. Remote sensing is a powerful technique for the monitoring of water bodies. To interpret the remotely sensed data, however, knowledge of the optical properties of the water constituents is needed. One of the most important of these is the volume scattering function, which describes the angular distribution of light scattered by a sample. This thesis presents the first measurements of volume scattering functions for Australian waters. Measurements were made on around 40 different samples taken from several locations in the Gippsland lakes and the Great Barrier Reef. The measurements were made by modifying an existing static light scattering spectrometer in order to accurately measure the volume scattering functions. The development of the apparatus, its calibration and automation, and the application of a complex series of post-acquisition data corrections, are all discussed. In order to extrapolate the data over the full angular range, the data was analysed using theoretical curves calculated for multi-modal size distributions using Mie light scattering theory applied to each data set. From the Mie fits the scattering and backscattering coefficients were calculated. These were compared with scattering coefficients measured using in situ sensors ac-9 and Hydroscat-6, and with values from the literature. The effect of chlorophyll a concentrations on the scattering coefficients was examined, and a brief investigation of the polarisation properties of the samples was also undertaken. Finally the angular effects on the relationship between the backscattering coefficient and the volume scattering function were investigated. This is important as in situ backscattering sensors often assume that measuring at a single fixed-angle is a good approximation for calculating the backscattering coefficient. This assumption is tested, and the optimal measurement angle determined.

To date, there exists no complete, computationally efficient, physics-based model to compute the radar backscatter from forest canopies. Several models attempt to predict the backscatter coefficient for random forest canopies by using the Vector Radiative Transfer (VRT) Theory with success, however, these models often rely on purely time-harmonic formulations and approximations to integrals. Forms of VRT models have recently been developed which account for a Gaussian pulse incident waveform, however, these models often rely heavily on very specific and obfuscated approximations to solve the associated integrals. This thesis attempts to resolve this problem by outlining a method by which existing, proven, time harmonic solutions to the VRT equation can be modified to account for arbitrary pulse waveforms through simple path delay method. These techniques lend physical insight into the actual scattering mechanisms behind the returned waveform, as well as offer explanations for why approximations of previous authors' break down in certain regions. Furthermore, these radiative transfer solutions can be reformulated into a convolutional model which is capable of quickly and accurately predicting the radar return of random volumes. A brief overview of radiative transfer theory as it applies to remote sensing is also given. / Master of Science

Co-located measurements of acoustic backscatter and temperature/velocity microstructure are used to confirm theoretical predictions of sound scatter from oceanic turbulence. The data were collected with a torpedo-shaped vehicle carrying four shear probes and two thermistors on its nose, and forward-looking 44.7 and 307 kilohertz echosounders (mounted 20 centimetres below the turbulence sensors). The vehicle was towed through the stratified turbulence that forms tidally over the lee side of a sill in a British Columbia fjord. Conventional downward-looking echosounder measurements were also made with a 100 kilohertz sounder mounted in the ship’s hull. Populations of amphipods, euphausiids, copepods and gastropods were present in the fjord (sampled with 335-micrometre mesh vertical net-hauls) and could be seen in the sounder data. These plankton net-hauls indicated that there were too few zooplankton in the turbulent regions to account for the scattering intensity. At both 44.7 and 307 kilohertz, scatter that is unambiguously correlated with turbulence was observed. Turbulent scatter is much stronger at the higher frequency, illustrating the mportance of salinity microstructure—long neglected in turbulent scattering models—and shedding some light on the form of the turbulent temperature-salinity co-spectrum. The turbulent temperature-salinity co-spectrum has never been measured directly. Although several models have been proposed for the form of the co-spectrum, they all produce unsatisfactory results when applied to the turbulent scattering equations (either predicting negative scattering cross-sections in some density regimes or predicting implausible levels of correlation between temperature and salinity at some scales). A new co-spectrum model is proposed and shown to be not only physically plausible in all density regimes, but also in reasonable agreement with the scattering data. At 307 kilohertz, the backscatter is mostly from salinity microstructure and, depending on the strength of the stratification, can be as strong as—or stronger than—the signal from a zooplankton scattering layer. This could easily confound zooplankton biomass estimates in turbulent regions. The two targets’ different natures (discrete targets versus a volume effect) often allow them to be distinguished even when they occur simultaneously. The key is sampling the same targets at multiple ranges. At long-range, discrete targets have a constant volume scattering strength proportional to their number density. The sampling volume, however, decreases as the targets approach the sounder. At some range there will be only one (or no) target in the sampling volume and the volume scattering strength will increase (or disappear) as the target continues to near the sounder. Turbulence, as a volume scattering effect, has no range dependence to its volume scattering strength. Thus, by examining the scattering nature at close range we can distinguish discrete targets (like zooplankton) from turbulence.