In this thesis, design details of binary irregular Low-Density Parity-Check (LDPC) codes are investigated. We especially focus on the trade-off between the average variable node degree, wa, and the number of length-6 cycles of an irregular code. We observe that the performance of the irregular code improves with increasing wa up to a critical value, but deteriorates for larger wa because of the exponential increase in the number of length-6 cycles. We have designed an irregular code of length 16,000 bits with average variable node degree wa=3.8, that we call &lsquo / 2/3/13&rsquo / since it has some variable nodes of degree 2 and 13 in addition to the majority of degree-3 nodes. The observed performance is found to be very close to that of the capacity approaching commercial codes. Time spent for decoding 50,000 codewords of length 1800 at Eb/No=1.6 dB for an irregular 2/3/13 code is measured to be 19% less than that of the regular (3, 6) code, mainly because of the smaller number of decoding failures.

Sonar is the traditional method of underwater target detection and tracking. However, using traditional sonar arrays may be difficult and impractical in some mission-critical scenarios as they require a ship or a submersible to be mounted on or towed by. Alternatively, Underwater Acoustic Sensor Networks (UW-ASN) offer a promising solution approach. In this thesis, a target tracking algorithm for UW-ASN, Three-Dimensional Underwater Target Tracking (3DUT) is presented. The objective of 3DUT is to collaboratively accomplish accurate tracking of underwater targets with minimum energy expenditure. Based on the time-of-arrival (ToA) of the echoes from the target after transmitting acoustic pulses from the sensors, the ranges of the nodes to the target are determined, and trilateration is used to obtain the location of the target. The location and the calculated velocity of the target are then exploited to achieve tracking. In order to realize energy-effective target tracking, 3DUT incorporates a new target movement-based duty cycle mechanism. To avoid rapid depletion of energy resources of boundary nodes due to continuous surveillance, 3DUT employs an adaptive procedure to find, designate, and activate new boundary nodes. Performance evaluation shows that 3DUT is a promising alternative to the traditional sonar based target tracking approaches especially for on-demand surveillance applications.

In traffic radar system, Frequency Modulated Continuous Wave (FMCW) will be used since these radars are preferred in short distance and high range resolution systems. The system to be constructed is not only a system operating with Doppler principle and detection of speed / on the contrary a functional radar is planned to be produced. In various traffic radars in use, Doppler shift constituted by the targets causing high reflection within detection field is measured and the measured speed corresponding to this shift is seen to exceed the limits. In case of cars more than one, their speeds cannot be measured separately. In this FMCW Radar system, it is possible to identify the targets&rsquo / distance and speed. The speed information of the target will be specified by Doppler frequency and also as a result of position monitoring, the speed will be determined out of the position change occurring in the unit time. These features, in multi lane road, will be used both for different lanes and also for the cars moving at the same lane but in different ranges. The radar system designed in this study is an easy to use, low power consuming device which can be mounted into the car. Only the active part of the system is off the shelf products and the other RF cards are designed and produced. As a result, a low cost traffic radar will be produced

In this thesis, we study the performance of an antenna switching (AS) system in comparison to an Alamouti coded system. We analyze the outage probabilities and propose minimum mean-squared error based iterative equalizers for both systems. We see from the outage probability analysis of both systems that the AS system may achieve the same diversity order of the Alamouti coded scheme contingent on the transmission rate and constellation size. In the proposed receiver, MMSE equalization and channel decoding are jointly carried out in an iterative fashion. We use both hard and soft decision channel decoders in our simulations. It is observed that the Alamouti based scheme performs better when the channel state information is perfect. The Alamouti scheme also performs better than the AS scheme when the channel state information is imperfect in hard decision channel decoder case and a random interleaver is used. On the other hand, if a random interleaver is not used, AS scheme performs remarkably better than the Alamouti scheme in hard decision channel decoder case. In a soft decision channel decoder case, when the channel state information is imperfect, the AS scheme performs approximately a 2 dB better than the Alamouti scheme. Moreover, there is approximately a 3 dB performance gain if a soft decision channel decoder is used instead of hard decision.

In practice, there exist many error sources which distort the antenna array pattern. For example, elements of antenna arrays influence each other (known as mutual coupling), mismatches in cables and element positions affects the antenna radiation pattern and also unequal gain and phase characteristics of RF receiver distorts the received signal. These effects generally degrade the array performance. They cause an increase in sidelobe levels with an accompanying decrease in gain. Also, these errors limit the performance of direction finding (DF) algorithms. So, in order to have low sidelobe level, good performance in direction finding and beamforming, calibration is necessary. In the literature, there exist many algorithms proposed for the calibration of errors. Calibration method used in this thesis assumes that there is a linear transformation between ideal signal and measurements. Calibration matrix is formed by using measurements. In this work, we look for the adequate number of measurements for successful calibration. Performance of calibration method may depend on the angle interval from which measurements are taken. So, the width of the data collection angle interval is also studied. Moreover, in real life, measurements can be collected from equally or randomly spaced angles. Does it affect the performance of calibration? The answer of this question is also inspected in this thesis. Additionally, the performance of algorithm under noise is studied. Performance evaluation is done for both elevation and azimuth sectors. Simulations are carried out on MATLABTM and Ansoft HFSS software package.

Energy or DFT detector using a fixed window size is very efficient when signal start time and duration is matched with that of the window&#039 / s. However, in the case of unknown signal duration, the performance of this detector decreases. For this scenario, a detector system composed of multiple windows may be preferred. Window sizes of such a system will also be fixed beforehand but they will be different from each other. Therefore, one of the windows will better match the signal duration, giving better detection results. In this study, multiple window detectors are analyzed. Their false alarm and detection probability relations are investigated. Some exact and approximate values are derived for these probabilities. A rule of thumb for the choice of window lengths is suggested for the case of fixed number of windows. Detectors with overlapping window structure are considered for the signals with unknown delay. Simulation results are added for these types of detectors.

Conventional methods of CFAR detection always use windowing, in the sense that some number of cells are investigated and the target present/absent decision is made according to the composition of the cells in that window. The most commonly used versions of CFAR detection algorithms are cell averaging CFAR, smallest of cell averaging CFAR, greatest of cell averaging CFAR and order-statistics CFAR. These methods all use windowing to set the decision threshold. In this thesis, rather than using windowed CFAR algorithms, a new method of estimating the background threshold is presented, analyzed and simulated. This new method is called the Switching IIR CFAR algorithm and uses two IIR filters to accurately estimate the background threshold. Then, using a comparison procedure, one of the filters is selected as the current threshold estimate and used. The results are seen to be satisfactory and comparable to conventional CFAR methods. The basic advantages of using the SIIR CFAR method are computational simplicity, small memory requirement and acceptable performance under clutter edges and multiple targets.

A complex exponential waveform embedded in white noise can be optimally detected by matched filtering which is equivalent to Discrete Fourier Transform (DFT). However, if the input includes multiple complex exponentials, the DFT processing is not optimal. The frequency spectrum of the complex exponential signal with finite observation interval is not impulse. The spectrum includes side-lobes called spectral leakage.Because of the strong side-lobes, weak components can be masked, or side-lobes can be interpreted as independent complex exponentials causing false alarms. The conventional approach is to suppress side-lobes by using an amplitude weighting function, called a window function. However, windows reduce the signal to noise ratio at the output and also widens the main lobe in the spectrum resulting in a loss of frequency resolution. In this thesis, the problem of detection of a complex exponential signal under a secondary complex exponential interference is investigated. Alternative windowing techniques such as spatially variant apodization (SVA), dual apodization (DA) are studied in the context of detection of weak sinusoids under strong sinusoidal interference. The detection performance of SVA and DA is compared with the conventional methods and the optimal detector.

In this thesis a single stage detector logarithmic video amplifier is designed with a dynamic range of 40dB in 2-6GHz frequency band. Since the detector logarithmic video amplifier (DLVA) is used to convert the power of the RF signals to video voltages in logarithmic scale, it can be regarded as a logarithmic converter instead of logarithmic amplifier. The design is composed of two main parts: The Schottky diode detector rectifies the incoming RF signal and produces a video voltage and the logarithmic amplifier transforms the scale of the video voltage from linear scale to logarithmic scale in order to observe the RF signals with a wide amplitude range. The approximation of the logarithmic function is obtained by the summation of the output currents of the differential amplifiers operating as logarithmic stages. Offset voltage of the DLVA is minimized in order to obtain maximum sensitivity / this makes the detection of RF signals with low power possible. The study is composed of mainly three parts: First, brief information about logarithmic amplification techniques is given and the circuit architecture is developed for logarithmic amplification and video detection, second these circuits are simulated and finally the design is implemented and tested.

In this thesis, we considered the deconvolution problem when the channel is known a priori. LSE and MSE optimum solutions are investigated with deterministic and statistical approaches. We derived closed form LSE expressions and investigated the factors that affect the FIR inverse filters. It turns out that, minimum LSE can be obtained when the system zeros are distributed homogeneously on the z-plane. We proposed partition-based FIR-IIR inverse filters. The selection of FIR and IIR parts is based on partitioning the channel zeros into two regions and using the specified channel zeros to design the best delay FIR and all pole IIR inverse filters. Three methods for partitioning are presented, namely unit circle-based, ring-based and optimum-partitioning. It turns out that ring-based and optimum-partitioning FIR-IIR inverse filter performs better than the best delay FIR inverse filter for the same complexity by about 4-5 dB. For noisy observations, it is shown that, noise should also be considered in the delay selection and partitioning. We extended our results for the design of MSE optimum statistical inverse filters. It is shown that best delay FIR-IIR inverse filters are less sensitive to the estimation errors compared to the IIR Wiener filters and they perform better than the FIR Wiener filters. Furthermore, they are always causal and stable making them suitable for real-time implementations. When the statistical and deterministic filters are compared, it is shown that for low SNR statistical filters perform better by about 1-2 dB, while deterministic filters perform better by about 0.5-1 dB for high SNR