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In this work, we propose a new method to improve the dynamic range performance of the Modulated Wideband Converter (MWC), which is multi-channel sampling system for digitizing wideband sparse signals below the Nyquist limit without loss of information by using compressive sensing techniques. MWC achieves high dynamic range assuming that subband frequency responses of the system are identical. However,...
In this work, we propose a framework which separates multi-emitter signals arriving to uniform linear antenna receiver system. Proposed model uses a combination of variational mode decomposition (VMD) and space alternating expectation maximization (SAGE) algorithms. Former one separates emitter signals and estimates their frequencies while in the second part channel parameters (relative phases, angle...
Attention-deficit/hyperactivity disorder (ADHD) is the most frequent diagnosis among children who are referred to psychiatry departments. Although ADHD was discovered at the beginning of the 20th century, its diagnosis is confronted with many problems. In this paper, a novel classification approach that discriminates ADHD and non-ADHD groups over the time-frequency domain features of ERP recordings...
IONOLAB is an interdisciplinary research group dedicated for handling the challenges of near earth environment on communication, positioning and remote sensing systems. IONOLAB group contributes to the space weather studies by developing state-of-the-art analysis and imaging techniques. On the website of IONOLAB group, www.ionolab.org, four unique space weather services, namely, IONOLAB-TEC, IRI-PLAS-2015,...
In this work, we propose a new method for online calibration of recently proposed Modulated Wideband Converter (MWC), which digitizes wideband sparse signals below the Nyquist limit without loss of information by using compressive sensing techniques. Our method requires a single frequency synthesizer card, which can generate clean tones along the operation band of the system, rather than much expensive...
In this study, optimal channel switching (time sharing) strategies are investigated under average power and cost constraints in order to maximize the average number of correctly received symbols between a transmitter and a receiver that are connected via multiple additive Gaussian noise channels. The optimal strategy is shown to perform channel switching either among at most three channels with full...
Synthetic Aperture Radar (SAR) has significance in many remote sensing applications. One of the main problems with SAR is the platform motion that causes defocusing in the reconstructed SAR image. To mitigate this problem, for particularly on imaging of fields that admit a sparse representation, various sparsity based techniques that either apply optimization procedures or greedy iterative solutions...
In this work we consider the problem of measurement matrix design for compressed 3-D Direction of Arrival (DoA) estimation using a sensor array with analog combiner. Since generic measurement matrix designs often do not yield optimal estimation performance, we propose a novel design technique based on the minimization of the Cramér-Rao Lower Bound (CRLB). We develop specific approaches for adaptive...
Synthetic Aperture Radar (SAR) has significant importance in many remote sensing applications. Errors due to the platform motion or measurement model uncertainties can cause degradations in the constructed SAR images. Most of the methods deal with the phase errors which cause defocusing on the image. For efficient processing of the measurements, they discretize the fast time-slow time plane and then...
Strecth Processing (SP) is a radar signal processing technique that provides high-range resolution with processing large bandwidth signals with lower rate Analog to Digital Converter(ADC)s. The range resolution of the large bandwidth signal is obtained through looking into a limited range window and low rate ADC samples. The target space in the observed range window is sparse and Compressive sensing(CS)...
Fractional Fourier Transform (FrFT) is the generalization of the ordinary Fourier Transform (FT) and a subclass of the Linear Canonical Transform (LCT). FrFT is used in many fields, where ordinary FT has already found applications, such as signal processing, optics, telecommunications, noise filtering, beamforming, and solution of differential equations.
It has been previously shown that chirp signals can be manipulated into a minimal time-bandwidth product (TBP) form in its so called natural domain, via fractionally Fourier transforming. Here we show that the time-bandwidth product (TBP) of the signal can be achieved in various other ways, under the class of Linear Canonical Transforms (LCT), which can be decomposed into shearing operations in time...
The 2-D signal representations of variables rather than time and frequency have been proposed based on either Hermitian or unitary operators. As an alternative to the theoretical derivations based on operators, we propose a joint fractional domain signal representation (JFSR) based on an intuitive understanding from a time-frequency distribution constructing a 2-D function which designates the joint...
In this paper, basic components of a digital communication system are simulated by a computer program. The simulation program is modular and flexible to incorporate any future additions and updates. The simulation program allows the user to choose from various channel models, transmitter and receiver antenna systems, modulation and channel coding techniques. A communication system is defined by various...
Computerized ionospheric tomography (CIT) is a method to investigate ionosphere electron density in two or three dimensions. This method provides a flexible tool for studying ionosphere. Earth based receivers record signals transmitted from the GPS satellites and the computed pseudorange and phase values are used to calculate Total Electron Content (TEC). Computed TEC data and the tomographic reconstruction...
A novel recursive framework for sparse reconstruction of continuous parameter spaces is proposed by adaptive partitioning and discretization of the parameter space together with expectation maximization type iterations. Any sparse solver or reconstruction technique can be used within the proposed recursive framework. Experimental results show that proposed technique improves the parameter estimation...
In patients with acute coronary syndrome, temporary chest pains together with changes in ECG ST segment and T wave occur shortly before the start of myocardial infarction. In order to diagnose acute coronary syndromes early, a new technique which detects changes in ECG ST/T sections is developed. As a result of implementing the developed technique to real ECG recordings, it is shown that the proposed...
Pulse-Doppler radar has been successfully applied to surveillance and tracking of both moving and stationary targets. For efficient processing of radar returns, delay-Doppler plane is discretized and FFT techniques are employed to compute matched filter output on this discrete grid. However, for targets whose delay-Doppler values do not coincide with the computation grid, the detection performance...
In this study, we consider performance improvement of an array of fixed estimators by using stochastic design techniques. The optimal design is investigated both in the absence and presence of an average power constraint. Two different performance criteria are considered; the average Bayes risk and the maximum Bayes risk. It is shown that the optimal stochastic parameter design results in a randomization...
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