Sharif Digital Repository

In this thesis, Particle Filter Methods are investigated in the context of moving targets tracking and the associated performance analysis. The application scope of this algorithm which is a particular case of Sequential Monte Carlo Method is far broader than tracking of moving targets. This algorithm can be used for mathematical calculations such as estimation of mathematical expectations, integrals, surface area of curves and many other mathematical calculations. In addition, it has applications in other branches of science like genetics. This algorithm is based on random sampling of a probability density function and resampling from the extracted samples. We change this algorithm in... 

One of the main challenges in data transmission is synchronization error. In practice there are solutions to this issue, but this incurs a cost that can not be neglected. Synchronization error consists of deletion, insertion and substitution. Investigation of such errors in a communication channel has been of a great concern in information theory. Furthermore, in many applications such as biology and data storage on disks, we observe synchronization errors. Deletion channel is defined as a channel in which input symbols are deleted with a probability d independently of each other, such that the order of symbols remains unchanged. In spite of attempts to find a closed form for the capacity of... 

In this thesis, we aim to explore the recovery of sparse signals from their compressive or random samples. At first, the Compressed Sensing (CS) recovery is considered and an iterative method with adaptive thresholding has been suggested which has superior performance compared to its counterparts in both reconstruction quality and simplicity. Then, random sampling, a special kind of compressive sensing, is investigated which is practically more efficient to be implemented than the compressive sampling scheme. A number of random sampling recovery techniques are offered based on sparsity which has very low computational complexity in a way that largedimensional signals can efficiently be... 

This thesis is dedicated to examine performance of compressive sensing based MIMO radar systems. MIMO radars have the ability to achieve higher target detection and parameter estimation as well as better performance in noisy and clutter environments than SISO or phased array radars. The need for high-speed analog to digital converters is one of the weaknesses in implementation of radar systems. With the advent of compressive sensing providing necessary guarantees for reconstruction of sparse signal using fewer samples than what Nyquist thorem describes, the need for such a high-speed converters that are either not available or too expensive is resolved. What allowes us to use compressive... 

Cognitive radio (CR) can successfully deal with the growing demand and scarcity of the wireless spectrum. To exploit limited spectrum efficiently, CR technology allows unlicensed users to access licensed spectrum bands. Since licensed users have priorities to use the bands, the unlicensed users need to continuously monitor the licensed users activities to avoid interference and collisions. How to obtain reliable results of the licensed users activities is the main task for spectrum sensing. Based on the sensing results, the unlicensed users should adapt their transmit powers and access strategies to protect the licensed communications. The requirement naturally presents challenges to the... 

Direction Of Arrival (DOA) estimation or direction finding refers to determining the arrival angle of a planar wave impinging on the array of sensors or antennas. The DOA information can be used by the smart antenna system for beam-forming and reliable data transmission. The problem of DOA estimation in propagating plane waves played a fundamental role in many applications including acoustic, wireless communication systems, navigation, biomedical imaging, radar/sonar systems, seismic sensing, and wireless 911 emergency call locating. In the conventional DOA estimating systems, an array of elements (antennas or sensors) is used that are colocated in a uniform pattern called, Uniform Linear... 

The emerging field of compressed sensing has found wide-spread applications in signal processing. Exploiting the sparsity of natural image signals on basis of a set of atoms called dictionary, one can find numerous examples for applications of compressed sensing in the field of image processing. One of these interesting applications is to help recover missing samples of a damaged or lossy image signal which is also known as image inpainting. There are dozens of reasons why an image may get damaged, for instance, during data transmission, some blocks of an image (or frames of a video ) may get lost due to error in the telecommunication channel (this is known as block-loss). In this case image... 

Due to its higher degrees of freedom in comparison with a Single-Input Single-Output (SISO) radar , a Multiple-Input Multiple-Output (MIMO) radar has superior resolution , higher accuracy in detection and estimation , and more flexibility in beamforming . As there are multiple receivers in a MIMO radar system , if we can reduce the sampling rate and send fewer samples to the common processing center , the cost can significantly be reduced . Sometimes , the problem is not even the cost . It is the technology issues of high sampling rates . The reduction in sampling rate can be achieved using Compressive Sensing (CS) or in a much simpler form Random Sampling (RS) . In CS , we take... 

Long-term effects of natural disasters, like earthquakes, in many cases have been reported high on transportation networks. Disruption in this lifeline network's performance imposes high social and economic costs upon the society. Undoubtedly, retrofitting the structures of all network links (or constructing new links) are practically impossible and economically infeasible. One solution to this problem is finding a method for determining the network's important links, and retrofitting their structures. Based on this concept, an optimization problem of network performance improvement under these stochastic events is introduced. In this problem, a link importance index for network links is...