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.

In this thesis, multiuser receivers for code division multiple-access (CDMA) downlink are studied under frequency selective fading channel conditions. The receivers investigated in this thesis attempt to estimate desired symbol as a linear combination of chip-rate sampled received signal sequence. A common matrix-vector representation of signals, which is similar to the model given by Paulraj et. al. is constructed in order to analyze the receivers studied in this thesis. Two receivers already well known in the literature are introduced and derived by using the common signal model. One of the receivers uses traditional matched filter and the other uses symbol-level linear minimum mean square error (MMSE) estimation. The receiver that uses traditional matched filter, also known as the conventional RAKE receiver, benefits from time diversity by combining the signal energy from multiple paths. The conventional RAKE receiver is optimal when multiple-access interference (MAI) is absent. Linear MMSE based receivers are known to suppress MAI and to be more robust to noise enhancement. The optimal symbol-level linear MMSE based receiver requires inversion of large matrices whose size is determined by either number of active users or spreading factor. These two parameters can be quite large in many practical systems and hence the computational load of this receiver can be a problem. In this thesis, two alternative low-complexity receivers, which are chip-level linear MMSE equalizer proposed by Krauss et. al. and interference-suppressing RAKE receiver proposed by Paulraj et. al., are compared with the linear full-rank MMSE based receiver and with the conventional RAKE receiver in terms of bit-error-rate performance. Various simulations are performed to evaluate the performance of the receivers and the parameters affecting the receiver performance are investigated.

Wireless sensor networks (WSN) have thus far been used for detection and tracking of static and mobile targets for surveillance and security applications. However, detection and tracking do not suffice for a complete satisfaction of these applications and an accurate target classification. To address this need, among various target classification methods, imaging of target yields the most valuable information. Nevertheless, imaging of mobile targets moving over an area requires networked and collaborative detection, tracking and imaging capabilities. With this regard, ultra-wideband (UWB) radar technology stands as a promising approach for networked target imaging over an area due to its unique features such as having no line-of-sight (LoS). However, the UWB wireless radar sensor network (WRSN) is yet to be developed for high quality imaging of mobile targets. In this thesis, an architecture for UWB wireless radar sensor network and a new collaborative mobile target imaging (CMTI) algorithm for UWB wireless radar sensor networks (WRSN) are presented. It is intended to accurately and efficiently obtain an image of mobile targets based on the collaborative eort of deployed UWB wireless radar sensor nodes. CMTI enables detection, tracking and imaging of mobile targets with a complete WRSN solution. CMTI exploits mobility of the target in the sensor field to build its own multi-static radar aperture. Performance evaluations reveal that CMTI obtains high quality radar image of mobile targets in WRSN with very low communication overhead and energy expenditure.

In this study, an automatic video segmentation and classification system based on audio features has been presented. Video sequences are classified such as videos with &ldquo / speech&rdquo / , &ldquo / music&rdquo / , &ldquo / crowd&rdquo / and &ldquo / silence&rdquo / . The segments that do not belong to these regions are left as &ldquo / unclassified&rdquo / . For the silence segment detection, a simple threshold comparison method has been done on the short time energy feature of the embedded audio sequence. For the &ldquo / speech&rdquo / , &ldquo / music&rdquo / and &ldquo / crowd&rdquo / segment detection a multiclass classification scheme has been applied. For this purpose, three audio feature set have been formed, one of them is purely MPEG-7 audio features, other is the audio features that is used in [31] the last one is the combination of these two feature sets. For choosing the best feature a histogram comparison method has been used. Audio segmentation system was trained and tested with these feature sets. The evaluation results show that the Feature Set 3 that is the combination of other two feature sets gives better performance for the audio classification system. The output of the classification system is an XML file which contains MPEG-7 audio segment descriptors for the video sequence. An application scenario is given by combining the audio segmentation results with visual analysis results for getting audio-visual video segments.

Multiple-input multiple-output (MIMO) systems have received much attention due to their multiplexing and diversity capabilities. It is possible to obtain remarkable improvement in spectral efficiency for wireless systems by using MIMO based schemes. However, sophisticated equalization and decoding structures are required for reliable communication at high rates. In this thesis, capacity achieving practical transceiver structures are proposed for MIMO wireless channels depending on the availability of channel state information at the transmitter (CSIT). First, an adaptive MIMO scheme based on the use of quantized CSIT and reduced precoding idea is proposed. With the help of a very tight analytical upper bound obtained for limited rate feedback (LRF) MIMO capacity, it is possible to construct an adaptive scheme varying the number of beamformers used according to the average SNR value. It is shown that this strategy always results in a significantly higher achievable rate than that of the schemes which does not use CSIT, if the number of transmit antennas is greater than that of receive antennas. Secondly, it is known that the use of CSIT does not bring significant improvement over capacity, when similar number of transmit and receive antennas are used / on the other hand, it reduces the complexity of demodulation at the receiver by converting the channel into noninterfering subchannels. However, it is shown in this thesis that it is still possible to achieve a performance very close to the outage probability and exploit the space-frequency diversity benefits of the wireless fading channel without compromising the receiver complexity, even if the CSIT is not used. The proposed receiver structure is based on iterative forward and backward filtering to suppress the interference both in time and space followed by a spacetime decoder. The rotation of multidimensional constellations for block fading channels and the single-carrier frequency domain equalization (SC-FDE) technique for wideband MIMO channels are studied as example applications.

RF and acoustic communications are widely used in terrestrial and underwater environments, respectively. This thesis examines the use of ultrasonic communication alternately in terrestrial applications. We first investigate the ultrasonic channel in order to observe whether reliable communication is possible among the ultrasonic nodes as an alternative to RF-based communications. Some key characteristics of the single-input-single-output (SISO) and single-inputmultiple- output (SIMO) ultrasonic channel are inspected with extensive experiments utilizing ultrasonic transmitters and receivers. Well known receiver diversity techniques are employed to combine the observations of multiple receiving ultrasonic transducers in a SIMO scheme and receiver diversity gain is attained. The thesis also covers the implementation of a receiver node by using a low-cost microcontroller.

With the developing radar technology, radars have been started to be used in the airborne platforms due to the need of fast, accurate and reliable information about the enemies. The most important and tactically needed information is the movements in an observation area. The detection of a ground moving target buried in a dense clutter environment from a moving air platform is a very challenging problem even today. The geometry of the operation, the course of the flight and structure of the clutter are the most effective parameters of this problem. There are some &ldquo / Ground Moving Target Indication&rdquo / (GMTI) techniques that have been studied for the last twenty years to overcome this problem. In this thesis, the simulation of some of these techniques in a realistic environment and the comparison of their performances are discussed. In this work, a GMTI simulator is developed to generate the environment containing the clutter and the noise signals, to locate and simulate the targets in this environment and to apply the GMTI techniques on the raw data generated by the simulator. The generation of the clutter signals including the internal clutter motion (ICM) for different types of clutter distributions is one of the most important parts of this thesis. The GMTI techniques being investigated throughout this thesis are &ldquo / Displaced Phase Center Antenna&rdquo / (DPCA), &ldquo / Along-Track Interferometry&rdquo / (ATI), &ldquo / Adaptive DPCA&rdquo / , &ldquo / Pre-Doppler Sigma-Delta STAP&rdquo / and &ldquo / Post-Doppler Sigma-Delta STAP&rdquo / techniques. These techniques are compared according to their clutter suppression and target detection performances under different environmental conditions.

In this thesis work, importance of radome structures for antenna systems is emphasized. Structural and electromagnetic requirements of various types of radome structures are analyzed and specific properties are given. Electromagnetic scattering analysis of sandwich type radome seams has been done. Total antenna system far electromagnetic field expression, which is the combination of original antenna far electromagnetic field and the scattered electromagnetic field of the framework of the sandwich radome structure has been found and simulated. To enhance electromagnetic transparency of sandwich type radomes two sandwich radome design methods are proposed which are expressed as Geometrical Randomization and Tuning the Seams. Electromagnetic scattering level minimizations advanced by these design methods are presented with related simulations.

Fractal is a recursively-generated object describing a family of complex shapes that possess an inherent self-similarity in their geometrical structure. When used in antenna engineering, fractal geometries provide multi-band characteristics and lowering resonance frequencies by enhancing the space filling property. Moreover, utilizing fractal arrays, controlling side lobe-levels and radiation patterns can be realized. In this thesis, the performance of Koch curve as antenna is investigated. Since fractals are complex shapes, there is no well&ndash / established for mathematical formulation to obtain the radiation properties and frequency response of Koch Curve antennas directly. The Koch curve antennas became famous since they exhibit better frequency response than their Euclidean counterparts. The effect of the parameters of Koch geometry to antenna performance is studied in this thesis. Moreover, modified Koch geometries are generated to obtain the relation between fractal properties and antenna radiation and frequency characteristics.