Abstract:
Polarization diversity in radar systems has opened a realm of new applications for imaging
radar systems that promises advancement in both the theoretical modeling and the
experimental characterization ofthe radar scattering behavior ofthe objects. Recent launches
of fully polarimetric space-borne SAR (Synthetic aperture radar) sensors are boon towards
the highly improved global imaging and mapping of the terrestrial covers. This in turn
requires the exploration of the existing methods and developing the newer ones for the
purpose.
Futuristic SAR missions are more focused towards deploying bistatic configuration, which
in spite of being subject to complex processing endow with more flexibility as compared to
the conventional monostatic missions. Bistatic SAR systems offer considerable degrees of
freedom in choosing transmitter and receiver trajectories that provide additional information
observations for the extraction of scene and target parameters. Experimental observations are
the primary access to support the conceptual studies of new remote sensing methods and
thus it naturally becomes the pressing need for the employment of bistatic geometry of radar
systems for various applications.
Taking an incentive of above SAR designs and their surpassing applications, the present
research work is divided in two parts. First part is devoted to the investigation and critical
analysis of the methodologies for landcover classification using polarimetric data and the
second part constitutes the characterization of surface parameters (i.e., surface roughness and
soil moisture) for facilitating their efficient retrievalwith bistaticmodeof the radar.
Research work is organized into seven chapters. First chapter provides a basic platform of
the research work by presenting a brief introduction, motivation and problem formulation
along with the details of the experimental and the satellite data sets. Some of the basic
concepts of polarimetry relevant for the work have been also discussed in the chapter. A
brief literature review of the related works is presented in chapter II.
Chapter III of the thesis explores the capability of polarimetric PALSAR (Phased Array type
L-band Synthetic aperture radar) data for landcover classification. In this chapter, analysis of
polarization signatures in linear and circular polarization for certain targets has been carried
in
out which lays the basis for fusion of linear and circular polarizations for classification. The
main focus of this work is to highlight the effect of circular polarization along with linear polarization on land cover classification. Linear polarization is confined to a single plane
containing the direction of propagation while for circular polarization; wave radiation is in
horizontal, vertical and planes between them [162]. Thus, circular polarization is found more
effective in examining the targets having different orientations or alignment with respect to
radar line of sight (LOS). Taking this in account the information about the target from both
linear and circular polarization can be merged to enhance the classification results. Thus, in
this chapter, initial linear basis has been converted to circular one(left/right handed circular).
Subsequently, polarization signatures have been plotted for few targets in both the bases and
the information gathered from each case has been compared [125]. Taking the ground of this
information, feature sets have been made on combining linear basis and circular basis
components together. Minimum distance classifier has been used to classify the image into
three broad land covers i.e., water, urban and agriculture. The analysis of the results led to
the conclusion that employing circular polarization with linear polarization can enhance the overall accuracy and classification accuracy ofcertain classes of interest.
Chapter IV presents a comparative study of different target decomposition techniques for
validating their suitability in classification of land covers with the help of few generic
supervised classifiers. A number of coherent and incoherent techniques exist for the
decomposition of targets based on scattering mechanisms. Except for few works, the need
for comparing the existing decomposition techniques for their suitability in terrain
classification remains an open area for research. Incoherent decomposition techniques are more suitable for describing natural targets but had been less reported. Since, the choice of a
suitable classification method for particular decomposition technique affects the
classification accuracy of various land covers. Therefore, in this chapter a detailed critical
analysis has been carried out to check the individual performance of each classification
method on the selected decomposition techniques for major land cover classification. Eigen
vector based H/A/alpha method and scattering model based decompositions have been used
[62, 212, 216, 218]. An effort has been made to compare the classification results obtained from the listed decomposition methods. For the purpose, algorithms have been applied on
the processed PALSAR data. Classification of the decomposed images from each of the
methods has been done using four supervised classifiers (parallelepiped, minimum distance,
Mahalanobis and maximum likelihood) [84, 169]. Ground truth data generated with the help
of ground survey points, topographic sheet and Google earth has been used for the
computation of classification accuracy. Parallelepiped classifier gave better classification
accuracy of water class for all the decomposition methods excluding H/A/Alpha. Minimum
distance/ Mahalanobis distance classifier gave better classification results for urban class.
Maximum likelihood classifier performed well as compared to other classifiers for
classification of agriculture class.
In chapter V, a novel effort has been made for the characterization of surface roughness
parameters i.e., vertical roughness (rms height), 's' and horizontal roughness (i.e., correlation
length), 7' at X-band for a dry bare sandy soil in bistatic specular direction. There is a dearth
of experimental investigations carried in bistatic mode using correlation length as the
roughness parameter along with rms height. Thus, the main aim of this work is to focus on
the importance of inclusion of correlation length as a roughness parameter alongwith rms
height using ground-based bistatic scatterometer data. Such an experimental investigation
thus paves the path for the effective modeling of roughness parameters that can be used for
the futuristic bistatic configurations. For the accomplishment of this task, observations have
been carried out in bistatic specular direction and some of the existing models have been
used for retrieving the roughness parameters. Stationary phase approximation (SPA model),
a theoretical model has been modified for the bistatic specular case for retrieving the
roughness parameters. A simplistic incidence angle approach developed initially for
emissivity [179] has been reformulated for bistatic scattering coefficient and used effectively
for the retrieval of surface parameters. An indoor experiment under controlled conditions
was performed and periodic rough surfaces were created by varying roughness in horizontal
and vertical directions. Experimental observations were taken over nine soil fields with s
(0.39-0.73 cm) and / (1.00-2.32 cm) varied under controlled conditions for different
incidence angles and like polarizations. A critical analysis of the angular response of
scattering coefficient with both roughness parameters has been done for both like
polarizations (HH- and W polarizations). It was noticed that W polarization provided
higher dynamic range of a° at different roughness than HH-polarization. Incidence angles
less than 50° showed better results for observing the effect of roughness parameters on a°,
however 40° was found as the best suitable incidence angle at a frequency of 10 GHz for
observing the effect of roughness parameters on scattering coefficient. Oh model (1992),
Dubois model (1995), modified SPA model and the reformulated Simplistic incidence angle
approach (SIA) have been applied to retrieve the surface parameters. SIA gave better results
than the existing models. The model suggested is the simple and efficient approach for such
type ofretrieval.
Chapter VI incorporates the variation of soil moisture along with the variation in surface
roughness parameters for bistatic observation. It presents a critical analysis of the nature of
the three soil parameters (i.e., soil moisture, horizontal roughness and the vertical roughness)
on the sensitivity of scattering coefficient in the specular direction. All the four models as
introduced in chapter V have been used for retrieval of soil parameters and compared. The
main aim of this work is to analyze the effect of correlation length with rms height at
different moisture contents for a bare soil surface. Bistatic configuration used for this
purpose was the same as used for chapter V. However, the observation set was increased to
1350 for the detailed study of the microwave response at the different field parameters (i.e.,
correlation length (/), rms height (s) and volumetric moisture content (mv)). Nine moisture
levels (0.072-0.228 cm3 cm"3) with each moisture level corresponding to three correlation
lengths and five rms heights (0.40-0.88 cm) have been considered. An incidence angle of60°
was found suitable for studying the individual and composite effect of soil parameters on
scattering coefficient for VV polarization. It was observed that for higher and moderate
moisture contents, dynamic range of specular scattering decreases and shows less variability
for moderate correlation lengths. However, dynamic range remains higher for higher
correlation lengths. This study is beneficial in soil moisture retrieval modeling. It provided
with the detailed analysis of the mutual and individual effect of roughness parameters and
soil moisture content on bistatic specular scattering coefficient.
Chapter VIIpresents the summary of contributions made in the thesis and the future scope of
the work.