The Interplanetary Magnetic Field (IMF) has a controlling effect on the Magnetosphere and Ionosphere. The objective in this work is to investigate the probable effects of IMF on Ionospheric and Geomagnetic response. To fulfill the objective the concept of an event has been created based on the polarity reversals and rate of change of the interplanetary magnetic field components, Bz and By. Superposed Epoch Method (SPE) was employed with the three event definitions, which are based on IMF Bz southward turnings ranging from 6 to 11 nT in order to quantify the effects of IMF By and Bz. For the first event only IMF Bz turnings were taken into account while for the remaining, positive and negative polarity for IMF By were added. Results showed that the increase in the magnitude of IMF Bz turnings increased the drop of F layer critical frequency, f0F2. The drop was almost linear with the increase in magnitude of polarity reversals. Reversals with a positive IMF By has resulted in the continuation of geomagnetic activity more than 4 days, that is to say, the energy, that has penetrated as a consequence of reversal with a positive By polarity, was stored in outer Magnetosphere,whereas, with a negative IMF By the energy was consumed in a small time scale. At the second step of the work, although conclusions about geomagnetic activity could be done, as a consequence of data gaps for f0F2 in addition to having low numbers of events, characterization of f0F2 due to constant IMF By polarity could not be accomplished. Thus, a modeling attempt for the characterization of the response due to polarity reversals of IMF components with the Genetic Programming was carried out. Four models were constructed for different polarity reversal cases and they were used as the components of one general unique model. The model is designed in such a way that given 3 consecutive value of f0F2, IMF By and IMF Bz, the model can forecast one hour ahead value of f0F2. The overall model, GETY-IYON was successful at a normalized error of 7.3%.

In this thesis, the problem of Angle of Arrival estimation of radar signals with Time Difference of Arrival method in an outdoor land multipath environment with limited line of sight is analyzed. A system model is proposed. Effects of system, channel and radar parameters on the Angle of Arrival estimation performance are investigated through Monte Carlo simulations. Improving effect of utilization of diversity on the estimation performance is observed. Performances of the space diversity with noncoherent and selective combining are compared. Finally a realistic scenario is studied and performance of the proposed system is investigated.

The feasibility of Ultra Wide Band (UWB) through the wall surveillance system is studied in this thesis. The transmitter and receiver architectures are discussed and an experimental set-up is constructed to verify the theory of UWB sensing. The constructed system has 80 mW peak, 6 uW average transmit power and 500 kHz PRF and a range resolution better than 1 cm. Using the experimental set-up, two problems are examined. The first problem is the respiration rate detection problem. It has been shown that the respiration rate can be accurately estimated and the signs of vital activity can be determined behind the wall. The second problem studied in this thesis is the through the wall imaging problem. The imaging system is based on the construction of a synthetic aperture by sliding the transmit-receive antenna pair along the cross range direction. The cross range resolution is improved by applying a migration algorithm to the collected data. It has been shown that imaging of a scene 8 meters in range, behind a wall of 20 cm thickness is possible with the available power.

In this study, various jamming techniques and their effects on detection and tracking performance have been investigated through a radar receiver simulation that models a search radar for target acquisition and single-target tracking radar during track operation. The radar is modeled as looking at airborne targets, and hence clutter is not considered. Customized algorithms have been developed for the detection of target azimuth angle, range and Doppler velocity within the modeled geometry and chosen radar parameters. The effects of varying parameters like jamming-to-signal ratio (JSR) and jamming signal`s Doppler shift have been examined in the analysis of jamming effectiveness.

In this thesis, we investigate the basics of Low-Density Parity-Check (LDPC) codes over binary and non-binary alphabets. We especially focus on the message passing decoding algorithms, which have different message definitions such as a posteriori probabilities, log-likelihood ratios and Fourier transforms of probabilities. We present the simulation results that compare the performances of small block length binary and non-binary LDPC codes, which have regular and irregular structures over GF(2),GF(4) and GF(8) alphabets. We observe that choosing non-binary alphabets improve the performance with careful selection of mean column weight by comparing LDPC codes with variable node degrees of 3, 2.8 and 2.6, since it is effective in the order of GF(2), GF(4) and GF(8) performances.

Security and quality of service (QoS) issues in cluster-based wireless sensor networks are investigated. The QoS perspective is mostly at application level consisting of four attributes, which are spatial resolution, coverage, system lifetime and packet loss due to collisions. The addressed security aspects are message integrity and authentication. Under this scope, the interactions between security and service quality are analyzed with particular emphasis on the tradeoff between security and spatial resolution for channel capacity. The optimal security and spatial resolution levels which yield the best tradeoff are determined. In addition, a control strategy is proposed to achieve the desired quality of service and security levels during the entire operation of a cluster-based sensor network. Compared to the existing studies, the proposed method is simpler and has superior performance.

With the enhancement of the Radio signal communication systems, Wi-Fi technology become a &ldquo / de facto&rdquo / standard used in Campus areas such as hospitals and universities. Besides being used as a data communication method, Received Signal Strength Indicator (RSSI) is also used as a location tracking method. There are lots of studies enhancing the RSSI based location tracking. In this thesis we tried to generate a test environment as close to a real Wi-Fi network scenario as possible. Our aim is to implement a simple moving client among different wireless local area networks, which is tracked across the internet by a stationary client. We also assumed that there is a Network Address Translation (NAT) at both LAN internet edges.

Space-Time Adaptive Processing (STAP) is an effective method in Ground Moving Target Indicator (GMTI) operation of airborne radars. Clutter suppression is the key to successful MTI operation. Airborne radars are different than the ground based ones in regard to clutter due to the displacement of the platform during operation. When STAP methods are to be investigated, one needs to have accurate signal models while evaluating performance. In this thesis, a comprehensive received signal model is developed first for an airborne antenna array. The impacts of the aircraft motion and irregularities in it, aircraft displacement during reception, intrinsic clutter motion and radar parameters have been accounted in the model and incorporated into a simulator environment. To verify the correctness of the signal simulator, the classical DPCA approach and optimum STAP methods are inspected.

We have devised a processor for pulsed Doppler radars for multi-target detection in same folded range under land and moving clutter. To this end, we have investigated the estimation of parameters, i.e., frequencies, amplitudes, and phases, of complex exponentials that model target echoes under radar clutter characterized by antenna scanning modulation with observation limited to single snapshot, i.e., one burst. The Maximum Likelihood method of estimation is presented together with the bounds on estimates, i.e., Cram&eacute / r-Rao bounds. We have analyzed linear prediction, together with its efficient implementation invented by Tufts &amp / Kumaresan, and compared its performance to other high resolution frequency estimation algorithms all modified to run under clutter. The essential part of the work is that line spectra estimation techniques model the clutter process also as a complex exponential. In addition, linear prediction combined with linear time&ndash / invariant maximum Signal to Interference Ratio (SIR) processor is analyzed. A technique to determine the model order, which is required by the frequency estimation algorithms, is presented that does not distinguish between targets and clutter. Clutter region concept is introduced to identify targets from clutter. The possibility to use these algorithms for target classification is briefly explained after providing a literature survey on helicopter echoes.

We introduce a steepest-descent-like search algorithm for the design of Boolean functions, yielding multiple desirable cryptographic properties in their Walsh and autocorrelation spectra together. The algorithm finds some Boolean functions on 9, 10, 11, 13 variables with very good cryptographic properties unattained in the literature. More specifically, we have discovered 9-variable rotation symmetric Boolean functions (RSBFs) having nonlinearity of 241, which exceeds the bent concatenation bound and has remained as an open question in the literature for almost three decades. We have then shown that there is no RSBF having nonlinearity greater than 241, and that there are 8x189 many RSBFs having nonlinearity of 241, such that, among them there are only two that are different up to the affine equivalence. We also propose a generalization to RSBFs and dihedral symmetric Boolean functions (DSBFs), which improves the nonlinearity result of 9-variable Boolean functions to 242. Further, we classify all possible permutations (362, 880) on the input variables of 9-variable Boolean functions and find that there are only 30 classes, which are different with respect to the linear equivalence of invariant Boolean functions under some permutations. Some of these classes and their subsets yield new 9-variable Boolean functions having the nonlinearity of 242 with different autocorrelation spectra from those of the Boolean functions found in generalized RSBF and DSBF classes. Moreover, we have attained 13-variable balanced Boolean functions having nonlinearity of 4036 which is greater than the bent concatenation bound of 4032, and improves the recent result of 4034.