Frequency Modulated Continuous Wave (FMCW) radar has wide application areas in both civil and military use. The range resolution is a critical concept for these FMCW radars as for the other radar types. There are theoretical restrictions in the range resolution. In addition, the non-ideal properties of the modules used in the systems negatively affects the range resolution. The transmitter leakage, non-linear frequency sweep, FM to AM distortion and measurement errors are some of the critical non-ideal properties. The problems arising from these non-ideal properties further restrict the range resolution of FMCW radars. Another important concept for the range resolution that can be obtained from FMCW radars is the signal processing method. This thesis deals with the non-ideal properties of the system modules and techniques to reduce their effects on the range resolution. Furthermore, the signal processing methods used for FMCW radar signals and the possible improvement techniques for these methods are discussed. Moreover, a simple signal processing unit called zero crossing counter which can be used for short range FMCW radars is implemented and range resolution performance of this zero crossing counter is investigated by carrying out measurements on a prototype FMCW radar at 2200MHz.

In this study, a neural network(NN) based algorithm is proposed for real time multiple source tracking problem based on a previously reported work. The proposed algorithm namely modified neural network based multiple source tracking algorithm (MN-MUST) performs direction of arrival(DoA) estimation in three stages which are the detection, filtering and DoA estimation stages. The main contributions of this proposed system are: reducing the input size for the uncorrelated source case (reducing the training time) of NN system without degradation of accuracy and insertion of a nonlinear spatial filter to isolate each one of the sectors where sources are present, from the others. MN-MUST algorithm finds the targets correctly no matter whether the targets are located within the same angular sector or not. In addition as the number of targets exceeds the number of antenna elements the algorithm can still perform sufficiently well. Mutual coupling in array does not influence MN-MUST algorithm performance. iv MN-MUST algorithm is further improved for a cylindrical microstrip patch antenna array by using the advantages of directive antenna pattern properties. The new algorithm is called cylindrical patch array MN-MUST(CMN-MUST). CMN-MUST algorithm consists of three stages as MN-MUST does. Detection stage is exactly the same as in MN-MUST. However spatial filtering and DoA estimation stage are reduced order by using the advantages of directive antenna pattern of cylindirical microstrip patch array. The performance of the algorithm is investigated via computer simulations, for uniform linear arrays, a six element uniform dipole array and a twelve element uniform cylindrical microstrip patch array. The simulation results are compared to the previously reported works and the literature. It is observed that the proposed algorithm improves the previously reported works. The algorithm accuracy does not degrade in the presence of the mutual coupling. A uniform cylindrical patch array is successfully implemented to the MN-MUST algorithm. The implementation does not only cover full azimuth, but also improv the accuracy and speed. It is observed that the MN-MUST algorithm provides an accurate and efficient solution to the targettracking problem in real time.

In OFDM systems carrier frequency offset is observed due to Doppler shift and transmitter-receiver frequency mismatches. This offset induces ICI (Intercarrier Interference). In this thesis, repeated data methods and pilot-aided carrier frequency offset(CFO) estimation methods and windowing techniques are used to mitigate the frequency offset problem and a performance comparison is made between these ICI cancellation techniques. Repeated data methods use only half of the bandwidth for information transmission to eliminate the ICI at the receiver. We have implemented repeated data methods including Self cancellation scheme and Symmetric Symbol Repetition (SSR) schemes to overcome ICI problem. We have also implemented Adjacent Conjugate Symbol Repetiton (ACSR) and Symmetric Conjugate Symbol Repetiton (SCSR) methods to mitigate both phase rotations and ICI. CFO estimation and correction methods generally use pilot sequences. We implemented the &ldquo / Conventional Pilots&rdquo / and &ldquo / Clustered Pilots&rdquo / pilot-aided CFO estimation techniques for ICI cancellation. Furthermore, we also implemented a new scheme by using the odd symmetry between pilot symbols. Nyquist windowing techniques apply windowing at the receiver side. We have implemented second order polynomial class of Nyquist windows and Nyquist window with Franks pulse used to mitigate ICI. These ICI cancellation methods are compared in AWGN and multipath Rayleigh fading channel models in terms of BER and carrier to interference ratio. It is shown that repeated data methods shows better performances than pilot-aided CFO estimation methods with a cost of increased bandwidth usage especially in high SNR&rsquo / s.

In this thesis, a number of novel watermarking techniques for different 3D representations are presented. A novel watermarking method is proposed for the mono-view video, which might be interpreted as the basic implicit representation of 3D scenes. The proposed method solves the common flickering problem in the existing video watermarking schemes by means of adjusting the watermark strength with respect to temporal contrast thresholds of human visual system (HVS), which define the maximum invisible distortions in the temporal direction. The experimental results indicate that the proposed method gives better results in both objective and subjective measures, compared to some recognized methods in the literature. The watermarking techniques for the geometry and image based representations of 3D scenes, denoted as 3D watermarking, are examined and classified into three groups, as 3D-3D, 3D-2D and 2D-2D watermarking, in which the pair of symbols identifies whether the watermark is embedded-detected in a 3D model or a 2D projection of it. A detailed literature survey on 3D-3D watermarking is presented that mainly focuses on protection of the intellectual property rights of the 3D geometrical representations. This analysis points out the specific problems in 3D-3D geometry watermarking , such as the lack of a unique 3D scene representation, standardization for the coding schemes and benchmarking tools on 3D geometry watermarking. For 2D-2D watermarking category, the copyright problem for the emerging free-view televisions (FTV) is introduced. The proposed watermarking method for this original problem embeds watermarks into each view of the multi-view video by utilizing the spatial sensitivity of HVS. The hidden signal in a selected virtual view is detected by computing the normalized correlation between the selected view and a generated pattern, namely rendered watermark, which is obtained by applying the same rendering operations which has occurred on the selected view to the original watermark. An algorithm for the estimation of the virtual camera position and rotation is also developed based on the projective planar relations between image planes. The simulation results show the applicability of the method to the FTV systems. Finally, the thesis also presents a novel 3D-2D watermarking method, in which a watermark is embedded into 3-D representation of the object and detected from a 2-D projection (image) of the same model. A novel solution based on projective invariants is proposed which modifies the cross ratio of the five coplanar points on the 3D model according to the watermark bit and extracts the embedded bit from the 2D projections of the model by computing the cross-ratio. After presenting the applicability of the algorithm via simulations, the future directions for this novel problem for 3D watermarking are addressed.

In this study, novel methods for high-resolution radar target detection in non-Gaussian clutter environment are proposed. In solution of the problem, two approaches are used: Non-coherent detection that operates on the envelope-detected signal for thresholding and coherent detection that performs clutter suppression, Doppler processing and thresholding at the same time. The proposed non-coherent detectors, which are designed to operate in non-Gaussian and range-heterogeneous clutter, yield higher performance than the conventional methods that were designed either for Gaussian clutter or heterogeneous clutter. The proposed coherent detector exploits the information in all the range cells and pulses and performs the clutter reduction and thresholding simultaneously. The design is performed for uncorrelated, partially correlated and fully correlated clutter among range cells. The performance analysis indicates the superiority of the designed methods over the classical ones, in fully correlated and partially correlated situations. In addition, by design of detectors for multiple targets and making corrections to the conventional methods, the target-masking problem of the classical detectors is alleviated.

Method of Moments (MoM)/Green&rsquo / s function formulation is developed for the analysis of electromagnetic radiation from planar rectangular microstrip antennas with different feeding techniques. Investigated structures are microstrip line fed patch antenna, proximity coupled patch antenna and slot coupled patch antenna. For all these structures equivalent problems are defined. Then, integral equations where currents are the unknowns are obtained from boundary conditions and by using spectral domain representation of Green&rsquo / s functions. Finally, MoM is applied to convert these integral equations to a system of linear equations. Currents on the conducting surfaces as well as equivalent magnetic currents on the apertures are modeled as a sum of piecewise sinusoidal subdomain basis functions with unknown coefficients which are calculated by solving the system of linear equations. Based on the formulations provided in this study, a Fortran code is developed. Numerical results calculated by using the code are presented in the form of patch and line currents and input impedances. Presented results are in good agreement with the results given in the literature.

In satellite applications, a circularly polarized satellite antenna is desirable with a pattern that results in constant received power while the distance between the transmitter and the receiver is changing. The Circular Disk - Annular Ring (CDAR) antenna satisfies these requirements along with other requirements for the satellite antenna. The CDAR antenna is a combination of a Circular Disk and an Annular Ring patch antennas. In this thesis, a circularly polarized CDAR antenna that is fed from a single point is designed at the center frequency of 8.2 GHz. This antenna is investigated and optimized to ease the fabrication process. The design parameters are defined on this report and optimized by using an Electromagnetic Simulation software program. In order to verify the theoretical results, Circular Disk - Annular Ring Antenna is produced as a prototype. Measurements of antenna parameters, electromagnetic field and circuit properties are interpreted to show compliance with theoretical and simulation results. The values of deviation between theoretical and experimental results are also discussed.

In the first part, the topic of average channel capacity for Orthogonal Frequency Division Multiplexing (OFDM) under Rayleigh, Rician, Nakagami-m, Hoyt, Weibull and Lognormal fading is addressed. With the assumption that channel state information is known, we deal with a lower bound for the capacity and find closed computable forms for Rician fading without diversity and with Maximum Ratio Combining diversity at the receiver. Approximate expressions are also provided for the capacity lower bound in the case of high Signal to Noise Ratio. This thesis presents two simplified Maximum A Posteriori (MAP) channel estimators to be used in OFDM systems under frequency selective slowly varying Rayleigh fading. Both estimators use parametric models, where the first model assumes exponential frequency domain correlation while the second model is based on the assumption of exponential power delay profile. Expressions for the mean square error of estimations are derived and the relation between the correlation of subchannel taps and error variance is investigated. Dependencies of the proposed estimators&rsquo / performances on the model parameter and noise variance estimation errors are analyzed. We also provide approximations on the estimators&rsquo / algorithms in order to make the estimators practical. Finally, we investigate SER performance of the simplified MAP estimator based on exponential power delay profile assumption used for OFDM systems with QPSK modulation. The results indicate that the proposed estimator performance is always better than that of the ML estimator, and as the subchannel correlation increases the performance comes closer to that of perfectly estimated channel case.

This thesis presents a novel aspect and polarization invariant electromagnetic target recognition technique in resonance region based on use of MUSIC algorithm for the extraction of natural-resonance related target features. In the suggested method, the feature patterns called &ldquo / MUSIC Spectrum Matrices (MSMs)&rdquo / are constructed for each candidate target at each reference aspect angle using targets&rsquo / scattered data at different late-time intervals. These individual MSMs correspond to maps of targets&rsquo / natural-resonance related power distributions. All these patterns are first used to obtain optimal late-time interval for classifier design and a &ldquo / Fused MUSIC Spectrum Matrix (FMSM)&rdquo / is generated over this interval for each target by superposing MSMs. The resulting FMSMs include more complete information for target resonances and are almost insensitive to aspect and polarization. In case of multiple target recognition, the relative locations of a multi-target group and separation distance between targets are also important factors. Therefore, MSM features are computed for each multi-target group at each &ldquo / reference aspect/topology&rdquo / combination to determine the optimum late-time interval. The FMSM feature of a given multi-target group is obtained by the superposition of all these aspect and topology dependent MSMs. In both single and multiple target recognition cases, the resulting FMSM power patterns are main target features of the designed classifier to be used during real-time decisions. At decision phase, the unknown test target is classified either as one of the candidate targets or as an alien target by comparing correlation coefficients computed between MSM of test signal and FMSM of each candidate target.

In this thesis, we study the energy efficient coverage and connectivity problem in wireless sensor networks (WSNs). We try to locate heterogeneous sensors and route data generated to a base station under two conflicting objectives: minimization of network cost and maximization of network lifetime. We aim at satisfying connectivity and coverage requirements as well as sensor node and link capacity constraints. We propose mathematical formulations and use an exact solution approach to find Pareto optimal solutions for the problem. We also develop a multiobjective genetic algorithm to approximate the efficient frontier, as the exact solution approach requires long computation times. We experiment with our genetic algorithm on randomly generated problems to test how well the heuristic procedure approximates the efficient frontier. Our results show that our genetic algorithm approximates the efficient frontier well in reasonable computation times.