In this thesis, an Experimental Radar System is designed and constructed for use in experimental radar studies such as clutter measurement and target detection, both in the laboratory and outdoor. COTS laboratory equipments are utilized as hardware elements of the radar and MATLAB is used as signal processing and user interface software tool. Vector signal generator (as transmitter), spectrum analyzer with vector signal analysis (as receiver), a high power amplifier, a low noise amplifier, horn antennas and a computer are the hardware units of the system. Various transmit signals are generated and pulse Doppler processing is performed at the receiver side. The system is controlled through the user interface which runs on a PC.

The aim of this thesis is to improve the operational performance of the communication antennas mounted on complex platforms such as aircrafts and warships by arranging placements of these antennas. Towards this aim, primarily, in order to gain insight on the influence of geometrically simple structures composing the platform on antenna performance, a quarter wavelength monopole antenna placed at the center of a finite square ground plane is studied by using uniform Geometrical Theory of Diffraction (GTD). Besides, the change of far field radiation pattern and complex diffraction functions due to the variation of the width of a square ground plane is examined. Secondly, electromagnetic analysis of two Ultra High Frequency (UHF) antennas mounted on geometrically simple structures composing simplified F-4 aircraft is carried out by using transient solver of Computer Simulation Technology (CST) Microwave Studio&reg / (MWS), in order to conceive the influence of each structure on antenna performance. Then, electromagnetic analysis of these antennas mounted on simplified and original F-4 aircrafts is performed, in order to determine the optimal location of the lower UHF antenna (newly installed antenna) for the operational performance of this antenna to be optimum in terms of electromagnetic coupling and far field radiation pattern. Finally, electromagnetic analysis of the communication antennas mounted on a warship is performed by using transient solver of CST MWS&reg / , in order to determine the optimal locations of these antennas for the operational performance of these antennas to be optimum in terms of electromagnetic coupling and far field radiation pattern.

The performance of radar detection and imaging systems strongly depends on the characteristics of radar clutter. In order to improve the radar signal processing algorithms, successful analysis and modeling of radar clutter are required. For a successful model of radar clutter, both the spectral and statistical characteristics of the clutter should be revealed. Within the scope of this study, an experimental radar data acquisition system is established to analyze radar clutter. The hardware and the data processing system are first verified using generic signals and then a set of measurements is taken in the open terrain. In this thesis, the limitations and problems encountered during the establishment of the system are explained in detail. The spectral and statistical analyses performed on the recorded data are examined. The temporal and spatial behavior of the measured clutter data are explored. The hypothetical models proposed so far in the literature are tested on the experimental data and the fitting of models to the experimental data is confirmed using various goodness-of-fit tests. Finally, the results of the analyses are interpreted in the light of the radar system parameters and the characteristics of the illuminated terrain.

Localization and tracking objects or people in real time in indoor environments have gained great importance. In the literature and market, many different location estimation and tracking solutions using received signal strength indication (RSSI) are proposed. But there is a lack of information on the comparison of these techniques revealing their weak and strong behaviors over each other. There is a need for the answer to the question / &ldquo / which localization/tracking method is more suitable to my system needs?&rdquo / . So, one purpose of this thesis is to seek the answer to this question. Hence, we investigated the behaviors of commonly proposed localization methods, mainly nearest neighbors based methods, grid based Bayesian filtering and particle filtering methods by both simulation and experimental work on the same test bed. The other purpose of this thesis is to propose an improved method that is simple to install, cost effective and moderately accurate to use for real life applications. Our proposed method uses an improved type of sampling importance resampling (SIR) filter incorporating automatic calibration of propagation model parameters of logv distance path loss model and RSSI measurement noise by using reference tags. The proposed method also uses an RSSI smoothing algorithm exploiting the RSSI readings from the reference tags. We used an active RFID system composed of 3 readers, 1 target tag and 4 reference tags in a home environment of two rooms with a total area of 36 m&sup2 / . The proposed method yielded 1.25 m estimation RMS error for tracking a mobile target.

Effort to estimate unknown time-varying channels as a part of high-speed mobile communication systems is of interest especially for next-generation wireless systems. The high computational complexity of the optimal Wiener estimator usually makes its use impractical in fast time-varying channels. As a powerful candidate, the adaptive least mean squares (LMS) algorithm offers a computationally efficient solution with its simple first-order weight-vector update equation. However, the performance of the LMS algorithm deteriorates in time-varying channels as a result of the eigenvalue disparity, i.e., spread, of the input correlation matrix in such chan nels. In this work, we incorporate the L MS algorithm into the well-known bidirectional processing idea to produce an extension called the bidirectional LMS. This algorithm is shown to be robust to the adverse effects of time-varying channels such as large eigenvalue spread. The associated tracking performance is observed to be very close to that of the optimal Wiener filter in many cases and the bidirectional LMS algorithm is therefore referred to as near-optimal. The computational complexity is observed to increase by the bidirectional employment of the LMS algorithm, but nevertheless is significantly lower than that of the optimal Wiener filter. The tracking behavior of the bidirectional LMS algorithm is also analyzed and eventually a steady-state step-size dependent mean square error (MSE) expression is derived for single antenna flat-fading channels with various correlation properties. The aforementioned analysis is then generalized to include single-antenna frequency-selective channels where the so-called ind ependence assumption is no more applicable due to the channel memory at hand, and then to multi-antenna flat-fading channels. The optimal selection of the step-size values is also presented using the results of the MSE analysis. The numerical evaluations show a very good match between the theoretical and the experimental results under various scenarios. The tracking analysis of the bidirectional LMS algorithm is believed to be novel in the sense that although there are several works in the literature on the bidirectional estimation, none of them provides a theoretical analysis on the underlying estimators. An iterative channel estimation scheme is also presented as a more realistic application for each of the estimation algorithms and the channel models under consideration. As a result, the bidirectional LMS algorithm is observed to be very successful for this real-life application with its increased but still practical level of complexity, the near-optimal tracking performa nce and robustness to the imperfect initialization.

This dissertation is focused on developing a new passband behavioral model in order to account for asymmetric intermodulation distortion resulted from memory effect. First, a measurement setup is prepared to measure the AM/AM, AM/PM distortion, magnitudes and the phases of intermodulation (IMD) and fundamental (FUND) components which are created by the amplifier where phase is calculated only by measuring magnitudes. Then, responses of a sample amplifier are measured for different excitation situations (center frequency and tone spacing are swept). A new modeling technique, namely Odd Order Modeling (OOM), is proposed which has unequal time delay terms. The reason of unequal time delay addition is the change of effective channel length according to the average power passing through that channel. These unequal delays create asymmetry in the IMD components. General Power Series Expansion (GPSE) model is also extracted, OOM and GPSE model performances are compared by using NMSE metric. In order to improve model performance, even order terms with envelope of input are added. It is mathematically proven that even order terms with envelope of the input have contribution to IMD and FUND components&rsquo / . This improved version of modeling is named as Even Order modeling (EOM). EOM model performance is compared with the others&rsquo / performance for two-tone excitation measurement results. It is shown that EOM gives the most accurate result. Model performance is checked for unequal four-tone signal as well. EOM model is applied to baseband DPD circuit after making some modifications. Model linearization performance is compared with the performances of the other memory polynomial modeling techniques.

In wireless communications, knowledge of the channel coefficients is required for coherent demodulation. In this thesis, a blind channel estimation method based on the Lloyd-Max algorithm is proposed for single-tap fading channels. The algorithm estimates the constellation points for the received signal using an iterative least squares approach. The algorithm is investigated for fast-frequency hopping systems with small block lengths and operating under partial-band and partial-time jamming for both detecting the jammer and estimating the channel. The performance of the Lloyd-Max channel estimation algorithm is compared to the performance of pilot-based channel estimation algorithms which also use the least squares approach and non-coherent demodulation and decoding.

Cooperative relaying systems aim to improve weak communication links by exploiting the spatial diversity obtained by the statistically independent channels between relays and the destination. In this thesis a cooperative relaying scheme called the Opportunistic Multiple Relaying (OMR) is proposed with its special receiver structure. Unlike most relaying schemes in the literature, multiple relay nodes are allowed to transmit in nonorthogonal channels in OMR without requiring any control overhead for relay coordination. OMR is compared to a benchmark scheme called the Selection Relaying (SR) in which the relay node is preselected by the source before transmission according to the average channel quality information. It is observed that OMR performs significantly better than SR in terms of error performance.

In Wireless Sensor Networks, designing a low overhead routing protocol is crucial for prolonging network lifetime. Wireless sensor nodes depend on limited batteries and if they run out of battery, they cannot contribute to the sensing. There are lots of studies aimed at prolonging network lifetime. One of the methods to extend life time of the wireless sensor networks is clustering. In clustering approaches main aim is to prevent unnecessary messaging and decrease number of messages exchanged by aggregating messages. Clustering also contributes to prolong network life time by ruling the child node communications and therefore it decreases message loss caused by transmission collisions. Cluster heads in clusters schedule nodes for sending and receiving messages. In this thesis, a clustering approach based on queries disseminated by sinks is proposed. Two methods to prolong lifetime of sensor network by forming appropriate clusters and selecting suitable cluster heads is developed. Performance of the proposed methods is also evaluated with computer simulations.

In this thesis, image dynamic range enhancement methods are studied in order to solve the problem of representing high dynamic range scenes with low dynamic range images. For this purpose, two main image dynamic range enhancement methods, which are high dynamic range imaging and exposure fusion, are studied. More detailed analysis of exposure fusion algorithms are carried out because the whole enhancement process in the exposure fusion is performed in low dynamic range, and they do not need any prior information about input images. In order to evaluate the performances of exposure fusion algorithms, both objective and subjective quality metrics are used. Moreover, the correlation between the objective quality metrics and subjective ratings is studied in the experiments.