Matching Items (12)
Filtering by
- All Subjects: Radar
- All Subjects: RRAM
- Creators: Electrical Engineering Program
- Member of: Barrett, The Honors College Thesis/Creative Project Collection
- Member of: Theses and Dissertations
Description
In many systems, it is difficult or impossible to measure the phase of a signal. Direct recovery from magnitude is an ill-posed problem. Nevertheless, with a sufficiently large set of magnitude measurements, it is often possible to reconstruct the original signal using algorithms that implicitly impose regularization conditions on this ill-posed problem. Two such algorithms were examined: alternating projections, utilizing iterative Fourier transforms with manipulations performed in each domain on every iteration, and phase lifting, converting the problem to that of trace minimization, allowing for the use of convex optimization algorithms to perform the signal recovery. These recovery algorithms were compared on a basis of robustness as a function of signal-to-noise ratio. A second problem examined was that of unimodular polyphase radar waveform design. Under a finite signal energy constraint, the maximal energy return of a scene operator is obtained by transmitting the eigenvector of the scene Gramian associated with the largest eigenvalue. It is shown that if instead the problem is considered under a power constraint, a unimodular signal can be constructed starting from such an eigenvector that will have a greater return.
ContributorsJones, Scott Robert (Author) / Cochran, Douglas (Thesis director) / Diaz, Rodolfo (Committee member) / Barrett, The Honors College (Contributor) / Electrical Engineering Program (Contributor) / School of Mathematical and Statistical Sciences (Contributor)
Created2014-05
Description
Passive radar can be used to reduce the demand for radio frequency spectrum bandwidth. This paper will explain how a MATLAB simulation tool was developed to analyze the feasibility of using passive radar with digitally modulated communication signals. The first stage of the simulation creates a binary phase-shift keying (BPSK) signal, quadrature phase-shift keying (QPSK) signal, or digital terrestrial television (DTTV) signal. A scenario is then created using user defined parameters that simulates reception of the original signal on two different channels, a reference channel and a surveillance channel. The signal on the surveillance channel is delayed and Doppler shifted according to a point target scattering profile. An ambiguity function detector is implemented to identify the time delays and Doppler shifts associated with reflections off of the targets created. The results of an example are included in this report to demonstrate the simulation capabilities.
ContributorsScarborough, Gillian Donnelly (Author) / Cochran, Douglas (Thesis director) / Berisha, Visar (Committee member) / Wang, Chao (Committee member) / Barrett, The Honors College (Contributor) / Electrical Engineering Program (Contributor) / School of Mathematical and Statistical Sciences (Contributor)
Created2014-05
Description
Resistive Random Access Memory (RRAM) is an emerging type of non-volatile memory technology that seeks to replace FLASH memory. The RRAM crossbar array is advantageous in its relatively small cell area and faster read latency in comparison to NAND and NOR FLASH memory; however, the crossbar array faces design challenges of its own in sneak-path currents that prevent proper reading of memory stored in the RRAM cell. The Current Sensing Amplifier is one method of reading RRAM crossbar arrays. HSpice simulations are used to find the associated reading delays of the Current Sensing Amplifier with respect to various sizes of RRAM crossbar arrays, as well as the largest array size compatible for accurate reading. It is found that up to 1024x1024 arrays are achievable with a worst-case read delay of 815ps, and it is further likely 2048x2048 arrays are able to be read using the Current Sensing Amplifier. In comparing the Current Sensing Amplifier latency results with previously obtained latency results from the Voltage Sensing Amplifier, it is shown that the Voltage Sensing Amplifier reads arrays in sizes up to 256x256 faster while the Current Sensing Amplifier reads larger arrays faster.
ContributorsMoore, Jenna Barber (Author) / Yu, Shimeng (Thesis director) / Liu, Rui (Committee member) / Electrical Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2016-12
Description
This thesis outlines the hand-held memory characterization testing system that is to be created into a PCB (printed circuit board). The circuit is designed to apply voltages diagonally through a RRAM cell (32x32 memory array). The purpose of this sweep across the RRAM is to measure and calculate the high and low resistance state value over a specified amount of testing cycles. With each cell having a unique output of high and low resistance states a unique characterization of each RRAM cell is able to be developed. Once the memory is characterized, the specific RRAM cell that was tested is then able to be used in a varying amount of applications for different things based on its uniqueness. Due to an inability to procure a packaged RRAM cell, a Mock-RRAM was instead designed in order to emulate the same behavior found in a RRAM cell.
The final testing circuit and Mock-RRAM are varied and complex but come together to be able to produce a measured value of the high resistance and low resistance state. This is done by the Arduino autonomously digitizing the anode voltage, cathode voltage, and output voltage. A ramp voltage that sweeps from 1V to -1V is applied to the Mock-RRAM acting as an input. This ramp voltage is then later defined as the anode voltage which is just one of the two nodes connected to the Mock-RRAM. The cathode voltage is defined as the other node at which the voltage drops across the Mock-RRAM. Using these three voltages as input to the Arduino, the Mock-RRAM path resistance is able to be calculated at any given point in time. Conducting many test cycles and calculating the high and low resistance values allows for a graph to be developed of the chaotic variation of resistance state values over time. This chaotic variation can then be analyzed further in the future in order to better predict trends and characterize the RRAM cell that was tested.
Furthermore, the interchangeability of many devices on the PCB allows for the testing system to do more in the future. Ports have been added to the final PCB in order to connect a packaged RRAM cell. This will allow for the characterization of a real RRAM memory cell later down the line rather than a Mock-RRAM as emulation. Due to the autonomous testing, very few human intervention is needed which makes this board a great baseline for others in the future looking to add to it and collect larger pools of data.
The final testing circuit and Mock-RRAM are varied and complex but come together to be able to produce a measured value of the high resistance and low resistance state. This is done by the Arduino autonomously digitizing the anode voltage, cathode voltage, and output voltage. A ramp voltage that sweeps from 1V to -1V is applied to the Mock-RRAM acting as an input. This ramp voltage is then later defined as the anode voltage which is just one of the two nodes connected to the Mock-RRAM. The cathode voltage is defined as the other node at which the voltage drops across the Mock-RRAM. Using these three voltages as input to the Arduino, the Mock-RRAM path resistance is able to be calculated at any given point in time. Conducting many test cycles and calculating the high and low resistance values allows for a graph to be developed of the chaotic variation of resistance state values over time. This chaotic variation can then be analyzed further in the future in order to better predict trends and characterize the RRAM cell that was tested.
Furthermore, the interchangeability of many devices on the PCB allows for the testing system to do more in the future. Ports have been added to the final PCB in order to connect a packaged RRAM cell. This will allow for the characterization of a real RRAM memory cell later down the line rather than a Mock-RRAM as emulation. Due to the autonomous testing, very few human intervention is needed which makes this board a great baseline for others in the future looking to add to it and collect larger pools of data.
ContributorsDobrin, Ryan Christopher (Co-author) / Halden, Matthew (Co-author) / Hall, Tanner (Co-author) / Barnaby, Hugh (Thesis director) / Kitchen, Jennifer (Committee member) / Electrical Engineering Program (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
Description
RRAM is an emerging technology that looks to replace FLASH NOR and possibly NAND memory. It is attractive because it uses an adjustable resistance and does not rely on charge; in the sub-10nm feature size circuitry this is critical. However, RRAM cross-point arrays suffer tremendously from leakage currents that prevent proper readings in larger array sizes. In this research an exponential IV selector was added to each cell to minimize this current. Using this technique the largest array-size supportable was determined to be 512x512 cells using the conventional voltage sense amplifier by HSPICE simulations. However, with the increase in array size, the sensing latency also remarkably increases due to more sneak path currents, approaching 873 ns for the 512x512 array.
ContributorsMadler, Ryan Anton (Author) / Yu, Shimeng (Thesis director) / Cao, Yu (Committee member) / Electrical Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
The honors thesis presented in this document describes an extension to an electrical engineering capstone project whose scope is to develop the receiver electronics for an RF interrogator. The RF interrogator functions by detecting the change in resonant frequency of (i.e, frequency of maximum backscatter from) a target resulting from an environmental input. The general idea of this honors project was to design three frequency selective surfaces that would act as surrogate backscattering or reflecting targets that each contains a distinct frequency response. Using 3-D electromagnetic simulation software, three surrogate targets exhibiting bandpass frequency responses at distinct frequencies were designed and presented in this thesis.
ContributorsSisk, Ryan Derek (Author) / Aberle, James (Thesis director) / Chakraborty, Partha (Committee member) / Electrical Engineering Program (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
Description
We present in this paper a method to compare scene classification accuracy of C-band Synthetic aperture radar (SAR) and optical images utilizing both classical and quantum computing algorithms. This REU study uses data from the Sentinel satellite. The dataset contains (i) synthetic aperture radar images collected from the Sentinel-1 satellite and (ii) optical images for the same area as the SAR images collected from the Sentinel-2 satellite. We utilize classical neural networks to classify four classes of images. We then use Quantum Convolutional Neural Networks and deep learning techniques to take advantage of machine learning to help the system train, learn, and identify at a higher classification accuracy. A hybrid Quantum-classical model that is trained on the Sentinel1-2 dataset is proposed, and the performance is then compared against the classical in terms of classification accuracy.
ContributorsMiller, Leslie (Author) / Spanias, Andreas (Thesis director) / Uehara, Glen (Committee member) / Barrett, The Honors College (Contributor) / Electrical Engineering Program (Contributor)
Created2023-05
Description
The use of conventional weather radar in vulcanology leads to two problems: the radars often use wavelengths which are too long to detect the fine ash particles, and they cannot be field–adjusted to fit the wide variety of eruptions. Thus, to better study these geologic processes, a new radar must be developed that is easily reconfigurable to allow for flexibility and can operate at sufficiently short wavelengths.
This thesis investigates how to design a radar using a field–programmable gate array board to generate the radar signal, and process the returned signal to determine the distance and concentration of objects (in this case, ash). The purpose of using such a board lies in its reconfigurability—a design can (relatively easily) be adjusted, recompiled, and reuploaded to the hardware with none of the cost or time overhead required of a standard weather radar.
The design operates on the principle of frequency–modulated continuous–waves, in which the output signal frequency changes as a function of time. The difference in transmit and echo frequencies determines the distance of an object, while the magnitude of a particular difference frequency corresponds to concentration. Thus, by viewing a spectrum of frequency differences, one is able to see both the concentration and distances of ash from the radar.
The transmit signal data was created in MATLAB®, while the radar was designed with MATLAB® Simulink® using hardware IP blocks and implemented on the ROACH2 signal processing hardware, which utilizes a Xilinx® Virtex®–6 chip. The output is read from a computer linked to the hardware through Ethernet, using a Python™ script. Testing revealed minor flaws due to the usage of lower–grade components in the prototype. However, the functionality of the proposed radar design was proven, making this approach to radar a promising path for modern vulcanology.
This thesis investigates how to design a radar using a field–programmable gate array board to generate the radar signal, and process the returned signal to determine the distance and concentration of objects (in this case, ash). The purpose of using such a board lies in its reconfigurability—a design can (relatively easily) be adjusted, recompiled, and reuploaded to the hardware with none of the cost or time overhead required of a standard weather radar.
The design operates on the principle of frequency–modulated continuous–waves, in which the output signal frequency changes as a function of time. The difference in transmit and echo frequencies determines the distance of an object, while the magnitude of a particular difference frequency corresponds to concentration. Thus, by viewing a spectrum of frequency differences, one is able to see both the concentration and distances of ash from the radar.
The transmit signal data was created in MATLAB®, while the radar was designed with MATLAB® Simulink® using hardware IP blocks and implemented on the ROACH2 signal processing hardware, which utilizes a Xilinx® Virtex®–6 chip. The output is read from a computer linked to the hardware through Ethernet, using a Python™ script. Testing revealed minor flaws due to the usage of lower–grade components in the prototype. However, the functionality of the proposed radar design was proven, making this approach to radar a promising path for modern vulcanology.
ContributorsLee, Byeong Mok (Co-author) / Xi, Andrew Jinchi (Co-author) / Groppi, Christopher (Thesis director) / Mauskopf, Philip (Committee member) / Baumann, Alicia (Committee member) / Cochran, Douglas (Committee member) / Electrical Engineering Program (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
Description
The use of conventional weather radar in vulcanology leads to two problems: the radars often use wavelengths which are too long to detect the fine ash particles, and they cannot be field–adjusted to fit the wide variety of eruptions. Thus, to better study these geologic processes, a new radar must be developed that is easily reconfigurable to allow for flexibility and can operate at sufficiently short wavelengths.
This thesis investigates how to design a radar using a field–programmable gate array board to generate the radar signal, and process the returned signal to determine the distance and concentration of objects (in this case, ash). The purpose of using such a board lies in its reconfigurability—a design can (relatively easily) be adjusted, recompiled, and reuploaded to the hardware with none of the cost or time overhead required of a standard weather radar.
The design operates on the principle of frequency–modulated continuous–waves, in which the output signal frequency changes as a function of time. The difference in transmit and echo frequencies determines the distance of an object, while the magnitude of a particular difference frequency corresponds to concentration. Thus, by viewing a spectrum of frequency differences, one is able to see both the concentration and distances of ash from the radar.
The transmit signal data was created in MATLAB®, while the radar was designed with MATLAB® Simulink® using hardware IP blocks and implemented on the ROACH2 signal processing hardware, which utilizes a Xilinx® Virtex®–6 chip. The output is read from a computer linked to the hardware through Ethernet, using a Python™ script. Testing revealed minor flaws due to the usage of lower–grade components in the prototype. However, the functionality of the proposed radar design was proven, making this approach to radar a promising path for modern vulcanology.
This thesis investigates how to design a radar using a field–programmable gate array board to generate the radar signal, and process the returned signal to determine the distance and concentration of objects (in this case, ash). The purpose of using such a board lies in its reconfigurability—a design can (relatively easily) be adjusted, recompiled, and reuploaded to the hardware with none of the cost or time overhead required of a standard weather radar.
The design operates on the principle of frequency–modulated continuous–waves, in which the output signal frequency changes as a function of time. The difference in transmit and echo frequencies determines the distance of an object, while the magnitude of a particular difference frequency corresponds to concentration. Thus, by viewing a spectrum of frequency differences, one is able to see both the concentration and distances of ash from the radar.
The transmit signal data was created in MATLAB®, while the radar was designed with MATLAB® Simulink® using hardware IP blocks and implemented on the ROACH2 signal processing hardware, which utilizes a Xilinx® Virtex®–6 chip. The output is read from a computer linked to the hardware through Ethernet, using a Python™ script. Testing revealed minor flaws due to the usage of lower–grade components in the prototype. However, the functionality of the proposed radar design was proven, making this approach to radar a promising path for modern vulcanology.
ContributorsXi, Andrew Jinchi (Co-author) / Lee, Matthew Byeongmok (Co-author) / Groppi, Christopher (Thesis director) / Mauskopf, Philip (Committee member) / Cochran, Douglas (Committee member) / Baumann, Alicia (Committee member) / Electrical Engineering Program (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
Description
This Creative Project was carried out in coordination with the capstone project, Around the Corner Imaging with Terahertz Waves. This capstone project deals with a system designed to implement Around the Corner, or Non Line-of-Sight (NLoS) Imaging. This document discusses the creation of a GUI using MATLAB to control the Terahertz Imaging system. The GUI was developed in response to a need for synchronization, ease of operation, easy parameter modification, and data management. Along the way, many design decisions were made ranging from choosing a software platform to determining how variables should be passed. These decisions and considerations are discussed in this document. The resulting GUI has measured up to the design criteria and will be able to be used by anyone wishing to use the Terahertz Imaging System for further research in the field of Around the Corner or NLoS Imaging.
ContributorsWood, Jacob Cannon (Author) / Trichopoulos, Georgios (Thesis director) / Aberle, James (Committee member) / Electrical Engineering Program (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05