With the advent of life critical and real-time services such as remote operations over satellite, e-health etc, providing the guaranteed minimum level of services at every ground terminal of the satellite communication system has gained utmost priority. Ground terminals and the hub are not equipped with the required intelligence to predict and react to inclement and dynamic weather conditions on its own. The focus of this thesis is to develop intelligent algorithms that would aid in adaptive management of the quality of service at the ground terminal and the gateway level. This is done to adapt both the ground terminal and gateway to changing weather conditions and to attempt to maintain a steady throughput level and Quality of Service (QoS) requirements on queue delay, jitter, and probability of loss of packets. The existing satellite system employs the First-In-First-Out routing algorithm to control congestion in their networks. This mechanism is not equipped with adequate ability to contend with changing link capacities, a common result due to bad weather and faults and to provide different levels of prioritized service to the customers that satisfies QoS requirements. This research proposes to use the reported strength of fuzzy logic in controlling highly non-linear and complex system such as the satellite communication network. The proposed fuzzy based model when integrated into the satellite gateway provides the needed robustness to the ground terminals to comprehend with varying levels of traffic and dynamic impacts of weather.

Phased array antenna has been used for a variety of military and civil applications, over the past five decades. Being structurally conformal and flexible, phased array antenna is highly suitable for mobile applications. Besides, it can form the agile or shaped beams required for interference cancellation or multifunction systems. Moreover, the spatial power combination property increases the effective radiated power of a transmitter phased array system. Similarly, in a receiver phased array, beamforming increases the signal to noise ratio by coherent integration of the desired signals. Despite its impressive potentials and properties, phased array antenna has not become a commercial product yet. Cost and complexity of phased array antenna are beyond the scales of consumer electronics devices. Furthermore, calibration is an essential requirement of such a complex system, which is a fairly time-consuming process and requires skilled man power. Moreover, the narrow bandwidth of microwave components degrades the broadband performance of phased array system. Finally, the majority of the beamforming algorithms developed so far have preconditions, which make them unsuitable for a low-cost system. The objective of this thesis is to provide a novel cost-effective solution to minimize the system complexity of the future intelligent antenna systems, without sacrificing the performance. This research demonstrates that a powerful, robust beamforming algorithm, integrated in an efficient single-receiver architecture, constitutes the essence of a low-cost phased array antenna. Thus, a novel beamforming technique, called Zero-knowledge algorithm is developed. It is investigated, both theoretically and experimentally, that the proposed algorithm can compensate for the hardware errors and imperfections of the low-cost components of the system. Zero-knowledge beamforming algorithm possesses significant properties. Neither a priori knowledge of the incoming signal direction, nor the exact characteristics of the phase control network are required in this method. Proper adjustment of the parameters, makes this algorithm appropriate for mobile systems, particularly those installed on vehicles. The algorithm alleviates the drawbacks of analog phase shifters, such as imbalanced insertion loss and fabrication tolerances. Furthermore, this algorithm can serve as the core of a direction-of-arrival estimation technique, which senses the minor deflections of the array heading. For broadband applications optical delay lines must be used in the phase control network of the phased array systems, which are costly. Nevertheless, employing miniaturized delay lines can significantly reduce the device area, and consequently, the fabrication cost. Thus, in this research four types of miniaturized optical delay lines, designed in slow-wave structures, are analyzed, which can provide a large delay per length. In addition, two novel optical beamforming techniques, based upon the properties of Zero-knowledge algorithm, are developed for transmitter and receiver phased arrays.

Measurements by OSIRIS, an infrared imaging system that measures emission from excited-state molecular oxygen, are used to retrieve mesospheric ozone through a photochemical model. The design of the model and the spectral data used in the calculation of pho- tochemical production coe±cients are presented. The model has been run in a variety of modes to provide comparisons with measurements of excited-state molec- ular oxygen; it has been found that the model results are in excellent agreement with measurements. The model is used in conjunction with a retrieval scheme to estimate the con- centrations of mesospheric ozone from measurements made on a satellite platform. An analysis of the sensitivity of retrieved ozone to key model parameters is done, and it is shown that uncertainty in several kinetic reaction rates can signi¯cantly change the retrieved results. Comparisons are made for the ozone retrieved in this work and that from several other instruments that make similar measurements. The retrieved concentrations are shown to be in excellent agreement with results from other instruments. The present work provides a climatological database of mesospheric ozone and will provide useful comparisons with concurrent measurements of mesospheric ozone. The new data obtained in this work are in good agreement with expected results, and it is shown that the unprecedented high-spatial resolution of OSIRIS reveals interesting features that should be further investigated.

Wildlife habitat mapping strongly supports applications in natural resource management, environmental conservation, impacts of anthropogenic activity, perturbed ecosystem restoration, species-at-risk recovery and species inventory. Remote sensing has long been identified as a feasible and effective technology for large-area wildlife habitat mapping. However, existing and future uncertainties in remote sensing will definitely have a significant effect on relevant scientific research, such as the limitation of Landsat-series data; the negative impact of cloud and cloud shadows (CCS) in optical imagery; and landscape pattern analysis using remote sensing classification products. This thesis adopted a manuscript-style format; it addresses these challenges (or uncertainties) and opportunities through exploring the state-of-the-art optical and radar remotely sensed data for large-area wildlife habitat mapping, and investigating their feasibility and applicability primarily by comparison either on the level of direct remote sensing products (e.g. classification accuracy) or indirect ecological model (e.g. presence/absence and frequency of use model based on landscape pattern analysis). A framework designed to identify and investigate the potential remotely sensed data, including Disaster Monitoring Constellation (DMC), Landsat Thematic Mapper (TM), Indian Remote Sensing (IRS), and RADARSAT-2, has been developed. The chosen DMC and RADARSAT-2 imagery have acceptable capability of addressing the existing and potential challenges (or uncertainties) in remote sensing of large-area habitat mapping, in order to produce cloud-free thematic maps for the study of wildlife habitat. A quantitative comparison between Landsat-based and IRS-based analyses showed that the characteristics of remote sensing products play an important role in landscape pattern analysis to build grizzly bear presence/absence and frequency of use models.

Satellite IP networks are characterized by high bit error rates, long propagation delays, low bandwidth feedback links, and persistent fades resulting from varying weather patterns. A new unicast transport protocol is designed to address all the above challenges. Two new algorithms, Jump Start and Quick Recovery, are presented to replace the traditional Slow Start algorithm and to recover rapidly from multiple segment losses within one window of data. The characteristics of satellite IP networks also distinguish satellite multicasting from multicasting in terrestrial wirelined networks. A reliable data multicast transport protocol, TCP-Peachtree, is proposed to solve the acknowledgment implosion and scalability problems in satellite IP networks. Developments in space technology are enabling the realization of deep space missions. The scientific data from these missions need to be delivered to the Earth successfully. To achieve this goal, the InterPlaNetary Internet is proposed as the Internet of the deep space planetary networks, which is characterized by extremely high propagation delays, high link errors, asymmetrical bandwidth, and blackouts. A reliable transport protocol, TP-Planet, is proposed for data traffic in the InterPlaNetary Internet. TP-Planet deploys rate-based additive-increase multiplicative-decrease (AIMD) congestion control and replaces the inefficient slow start algorithm with a novel Initial State algorithm that allows the capture of link resources in a very fast and controlled manner. A new congestion detection and control mechanism is developed and a Blackout State is incorporated into the protocol operation. Multimedia traffic is also one part of the aggregate traffic over InterPlaNetary Internet backbone links and it has additional requirements such as minimum bandwidth, smooth traffic, and error control. To address all the above challenges, RCP-Planet is proposed. RCP-Planet consists of two novel algorithms, i.e., Begin State and Operational State. The protocol is based on a novel rate probing mechanism and a new rate control scheme to update the media rate smoothly based on the observed rate for the probing sequence.

Internal waves include soliton of period 10-20 minutes and tidal frequency waves. Large internal solitons with amplitude over 100 m were observed frequently in the South China Sea (SCS). There were convergence zones of 500-1000 m wide in the wave front of solitons which can be detected by satellite from the space. The hypothesis of this study is the internal wave signal can be extracted from the sea surface anomalies of satellite altimetry. Data analyzed include TOPEX/Poseidon altimeter from August 2002 to October 2005 in the northern SCS and Kuroshio regions. Methods applied include (1) standard deviation analysis, (2) harmonic analysis and (3) wavenumber spectrum analysis. The results show that¡]1¡^there is an annual variation in the sea surface height, which is explained due to water temperature changes in different seasons. (2) The results of harmonic analysis show that the amplitude of M2 aliasing is only a few centimeters on the sea surface. The different is small between internal active region and that of without. (3) The absolute values of slope, of internal wave energy and wavenumber spectrum, are 2-3 in the wave active region. This suggests that there are wave motions of scale 100 km or larger, which matches with the length scale of internal waves in the northern SCS.

In this thesis, we introduce a new class of problems, which we call Optimal Areal Positioning (OAP), and study a special form of these problems. OAPs have important applications in earth observation satellite management, tele-robotics, multi-camera control, and surveillance. In OAP, we would like to find the optimal position of a set of floating geometric objects (targets) on a two-dimensional plane to (partially) cover another set of fixed geometric objects (requests) in order to maximize the total reward obtained from covered parts of requests. In this thesis, we consider the special form of OAP in which targets and requests are parallel axes rectangles and targets are of equal size. A predetermined reward is associated with covering an area unit of each request. Based on the number of target rectangles, we classify rectangular OAP into two categories: Single Target Problem (STP) and Multi-Target Problem (MTP). The structure of MTP can be compared to the planar p-center which is NP-complete, if p is part of the input. In fact, we conjecture that MTP is NP-complete. The existing literature does not contain any work on MTP. The research contributions of this thesis are as follows: We develop new theoretical properties for the solution of STP and devised a new solution approach for it. This approach is based on a novel branch-and-bound (BB) algorithm devised over a reduced solution space. Branching is done using a clustering scheme. Our computational results show that in many cases our approach significantly outperforms the existing Plateau Vertex Traversal and brute force algorithms, especially for problems with many requests appearing in clusters over a large region. We perform a theoretical study of MTP for the first time and prove several theoretical properties for its solution. We have introduced a reduced solution space using these properties. We present the first exact algorithm to solve MTP. This algorithm has a branch-and-bound framework. The reduced solution space calls for a novel branching strategy for MTP. The algorithm has a main branch-and-bound tree with a special structure along with two trees (one for each axis) to store the information required for branching in the main tree in an efficient format. Branching is done using a clustering scheme. We perform computational experiments to evaluate the performance of our algorithm. Our algorithm solves relatively large instances of MTP in a short time.

Constellation reconfi guration consists of transforming an initial constellation of satellites into some final constellation of satellites to maintain system optimality. Constellations with phased deployment, changing mission requirements, or satellite failures would all benefi t from reconfi guration capability. The constellation reconfiguration problem can be broken into two broad sub-problems: constellation design and constellation transfer. Both are complicated and combinatorial in nature and require new, more efficient methods. Having reviewed existing constellation design frameworks, a new framework, the Elliptical Flower Constellations (EFCs), has been developed that offers improved performance over traditional methods. To assist in rapidly analyzing constellation designs, a new method for orbit propagation based on a sequential solution of Kepler's equation is presented. The constellation transfer problem requires an optimal assignment of satellites in the initial orbit to slots in the final orbit based on optimal orbit transfers between them. A new method for approximately solving the optimal two-impulse orbit transfer with fixed end-points, the so-called minimum Delta v Lambert's problem, is developed that requires the solution of a 4th order polynomial, as opposed to the 6th or higher order polynomials or iterative techniques of existing methods. The recently developed Learning Approach to sampling optimization is applied to the particular problem of general orbit transfer between two generic orbits, with several enhancements specifi c to this problem that improve its performance. The constellation transfer problem is then posed as a Linear Assignment Problem and solved using the auction algorithm once the orbit transfers have been computed. Constellations designed for global navigation satellite systems and for global communications demonstrate signifi cant improvements through the use of the EFC framework over existing methods. An end-to-end example of constellation recon figuration for a constellation with changing regional coverage requirements shows the effectiveness of the constellation transfer methods.

The distance of sound propagation in water is inversely proportional to the frequency; there for the low frequency noise generated by distance shipping contribute most to the low frequency components of the ocean ambient noise. In order to improve the performance of sonar application, understanding and predication shipping noise is important. In this study, noise data was collected by vertical line array (VLA), in South China Sea of Asian Seas International Acoustics Experiment (ASIEX) in 2001. Due to the limited access to the satellite imagery, and based on the assumption that fishing vessels in South China Sea has similar operational pattern and lighting in recent years, the night time satellite image data was acquired by Defense Meteorological Satellite Program DMSP - Operational Linescan System(DMSP-OLS) of 2005. Linear regression was analyzed between fishing light pixel distribution and low frequency noise level variation, fishing light was expressed in terms of total pixel number and total light intensity, and distance from fishing vessel to VLA was assumed by spherical and cylindrical spread. The results show high correlation between total light intensity and noise level, and cylindrical spreading is better assumption in shallow water on the continental shelf at low frequency. As a conclusion, this study successfully prove that by using the night satellite image, the low frequency fishing vessel noise can be predicted with reasonable accuracy.

<p>This thesis deals with the global aspects of plasmaconvection in the magnetosphere as measured by the low-altitudepolar orbiting Astrid-2 and FAST satellites. The major focus ison the electric field measurements, but they are alsocomplemented by magnetic field, ion and electron particle data,which is fundamental for the understanding of theelectrodynamics of the high-latitude auroral ovals and polarcap, which are the regions analysed here. The essential subjectof this thesis is the so-called magnetic reconnection processthat drives plasma convection in the Earth's magnetosphere. Itis shown that the ionospheric convection, being intimatelycoupled to the magnetospheric convection, responds in about15-25 min depending on geomagnetic activity after the arrivalof the solar wind at the magnetopause. It also responds on alonger time scale, around 55-75 min, which is interpreted asthe unloading of solar wind energy previously stored in thelarge-scale current system of the magnetotail. These resultshave been found previously using ionospheric parameters such asthe auroral electrojet AL index. What is new is that these sameresults are reproduced by using a discrete set of cross-polarpotential measurements. Using an extensive set of electric andmagnetic field data combined with particle precipitation datafrom the FAST satellite, it is shown that the reconnectionprocess can also be applied to explain features of sunwardplasma convection in the polar cap with a likely antiparallelmerging site in the lobe magnetopause region. The lobereconnection is found to depend strongly on IMF B_yand to coexist with dayside subsolar merging.Finally, a comparison is performed between the Weimer electricfield model and Astrid-2 electric field data. Empiricalelectric field models are important in understanding thecomplete convection pattern at any one time, something, whichcannot be provided by measurements from single satellites.</p><p><b>Keywords:</b>Satellite measurements, electric fields,magnetosphere, magneticreconnection, plasma convection, lobecell convection, empirical electric field models.</p>