Defense Notices


All students and faculty are welcome to attend the final defense of EECS graduate students completing their M.S. or Ph.D. degrees. Defense notices for M.S./Ph.D. presentations for this year and several previous years are listed below in reverse chronological order.

Students who are nearing the completion of their M.S./Ph.D. research should schedule their final defenses through the EECS graduate office at least THREE WEEKS PRIOR to their presentation date so that there is time to complete the degree requirements check, and post the presentation announcement online.

Upcoming Defense Notices

Jennifer Quirk

Aspects of Doppler-Tolerant Radar Waveforms

When & Where:


Nichols Hall, Room 129 (Apollo Auditorium)

Committee Members:

Shannon Blunt, Chair
Patrick McCormick
Charles Mohr
Alessandro Salandrino
Zsolt Talata

Abstract

The Doppler tolerance of a waveform refers to its behavior when subjected to a fast-time Doppler shift imposed by scattering that involves nonnegligible radial velocity. While previous efforts have established decision-based criteria that lead to a binary judgment of Doppler tolerant or intolerant, it is also useful to establish a measure of the degree of Doppler tolerance. The purpose in doing so is to introduce a Doppler "quasi-tolerant" trade-space that can ultimately inform automated/cognitive waveform design in increasingly complex and dynamic radio frequency (RF) environments. This idea of Doppler quasi-tolerance leads to the development of random FM (RFM) waveforms that retain a degree of Doppler tolerance while still providing the diversity of a nonrepeating waveform structure. The ensuing ambiguity functions split the delay/Doppler ridge into a variety of different patterns. Since these patterns are known at transmission, a strategy for appropriate coherent slow time combining is demonstrated in simulation. Separately, the application of slow-time coding (STC) to the Doppler-tolerant linear FM (LFM) waveform has been examined for disambiguation of multiple range ambiguities. However, using STC with non-adaptive Doppler processing often results in high Doppler "cross-ambiguity" side lobes that can hinder range disambiguation despite the degree of separability imparted by STC. To enhance this separability, a gradient-based optimization of STC sequences is developed, and a "multi-range" (MR) modification to the reiterative super-resolution (RISR) approach that accounts for the distinct range interval structures from STC is examined. The efficacy of these approaches is demonstrated using open-air measurements. Pulse agility is an alternative range disambiguation technique that relies on pulse-to-pulse waveform separability. Although pulse-agile waveforms are often uncorrelated and therefore amenable to range disambiguation, they may exhibit poor Doppler tolerance. To preserve Doppler tolerance and achieve separability, a class of hybrid waveforms is developed whereby a phase code is embedded on an LFM base waveform. A gradient-based optimization is developed for this waveform structure to achieve enhanced suppression of range-folded scattering in desired delay/Doppler regions. The Doppler tolerance and separability of the optimized waveforms are examined in simulation, and open-air measurements are used to demonstrate the range disambiguation capability.


Abdalla Hassan Eltom

Bringing Anytime Perception to Real Hardware: An Embedded Deployment of the Autoware Stack with Dynamic Resolution Scaling

When & Where:


Nichols Hall, Room 250 (Gemini Conference Room)

Committee Members:

Heechul Yun, Chair
Prasad Kulkarni
Shawn Keshmiri


Abstract

Deploying deep neural networks for perception on autonomous vehicles forces a compromise between how accurately the system perceives and how quickly it responds. This compromise is especially binding on embedded compute platforms, where limited processing power means a high-accuracy detector may fail to finish within the control loop's timing budget, leaving the vehicle to act on outdated information. Anytime perception offers a way to manage this by adjusting inference cost at runtime, but its benefits have so far been shown mainly in simulation, with little evidence from physical deployment.

This thesis provides that evidence. We take MURAL — a multi-resolution anytime LiDAR detector previously integrated into the Autoware stack and evaluated in the AWSIM simulator — and deploy it on a physical mid-size rover, running the full sensing-to-actuation pipeline on a single NVIDIA Jetson AGX Orin. Reaching a working deployment required substantial adaptation of a stack originally built for full-scale vehicles in simulation, from retargeting the vehicle model to rover scale to bringing the entire pipeline on-board a single embedded device.

By carrying the complete stack onto real hardware, this work makes it possible to evaluate anytime perception under the conditions it was designed for: a full autonomous-driving pipeline running on an edge device in the physical world. We assess, through end-to-end physical experiments, whether dynamically scaling detection resolution delivers a real performance benefit on embedded hardware — providing, to our knowledge, the first true evaluation of anytime perception for edge-deployed autonomous driving.


Logan Schmalz

A Framework for Controlled Key Release

When & Where:


Nichols Hall, Room 246 (Executive Conference Room)

Committee Members:

Perry Alexander, Chair
Drew Davidson
Sankha Guria


Abstract

Modern security relies heavily on public key cryptography, and private keys and secrets in general must be protected from attackers. Against a highly-capable adversary it is ideal to store secrets outside of main memory, which is easy on general purpose systems with the now widely-available Trusted Platform Module (TPM) 2.0. However, the lack of integration between the TPM and the OS makes protecting secrets with automated availability needs difficult. We develop a strategy to authenticate OS entities and protect TPM-stored secrets without restricting access to the TPM, using standard features available on Linux---SELinux, Integrity Measurement Architecture (IMA), Extended Verification Module (EVM), and Linux Unified Key Setup (LUKS).


Past Defense Notices

Dates

Gordon Ariho

Multipass SAR Processing for Ice Sheet Vertical Velocity and Tomography Measurements and Application of Reduced Rank MMSE to Spectrally Efficient Radar Design

When & Where:


Zoom Meeting, please contact jgrisafe@ku.edu for link

Committee Members:

Jim Stiles, Chair
John Paden (Co-Chair)
Shannon Blunt
Carl Leuschen
Emily Arnold

Abstract

First Topic: Ice sheets impact sea-level change and hence their response to climatic variations needs to be continually monitored and studied. We propose to apply multipass differential interferometric synthetic aperture radar (DInSAR) techniques to data from the Multichannel Coherent Radar Depth Sounder (MCoRDS) to measure the vertical displacement of englacial layers within an ice sheet. DInSAR’s accuracy is usually on the order of a small fraction of the wavelength (e.g. millimeter to centimeter precision is common) in monitoring ground displacement along the radar line of sight (LOS).  In the case of ice sheet internal layers, vertical displacement is estimated by compensating for the spatial baseline using precise trajectory information and estimates of the cross-track layer slope from direction of arrival analysis. Preliminary results from a high accumulation region near Camp Century in northwest Greenland and Summit Station in central Greenland are presented here. We propose to extend this work by implementing a maximum likelihood estimator that jointly estimates the vertical velocity, the cross-track internal layer slope, and the unknown baseline error due to GPS and INS errors. The multipass algorithm will be applied to additional flights from the decade long NASA Operation IceBridge airborne mission that flew MCoRDS on many repeated flight tracks. We also propose to improve the accuracy of tomographic swaths produced from multipass measurements and investigate the possibility to use focusing matrices to improve wideband tomographic processing.

Second Topic: With the increased demand for bandwidth-hungry applications in the telecommunications industry, radar applications can no longer enjoy the generous frequency allocations within the UHF band. Spectral efficiency, if achievable, leads to the freeing of portions of the radar bandwidth to facilitate spectrum sharing between radar and other wireless systems. A decrease in bandwidth leads to worse radar resolution. In certain scenarios, reduced resolution is acceptable, and bandwidth may be compromised for spectral efficiency. An iterative reduced rank MMSE algorithm based on marginal Fisher information is proposed and investigated to minimize the loss of resolution with the tradeoff of degraded side-lobe performance. The algorithm is applied to the radar measurement model with simulated range profiles and performance results discussed.


Kishanram Kaje

Complex Field Modulation in Direct Detection Systems

When & Where:


Zoom Meeting, please contact jgrisafe@ku.edu for link

Committee Members:

Rongqing Hui, Chair
Christopher Allen
Victor Frost
Erik Perrins
Jie Han

Abstract

 Even though fiber optics communication is providing a high bandwidth channel to achieve high speed data transmission, there is still a need for higher spectral efficiency, faster data processing speeds while reduced resource requirements due to ever increasing data and media traffic. Various multilevel modulation and demodulation techniques are used to improve spectral efficiency. Although, spectral efficiency is improved, there are other challenges that arise while doing so such as requirement for high speed electronics, receiver sensitivity, chromatic dispersion, operational flexibility etc. Here, we investigate complex high speed field modulation techniques in direct detection systems to improve spectral efficiency while focusing to reduce resources required for implementation, compensating for linear and nonlinear impairments in fiber optics communication systems.

We first demonstrated a digital-analog hybrid subcarrier multiplexing (SCM) technique which can reduce the requirement of high speed electronics such as ADC and DAC, while providing wideband capability, high spectral efficiency, operational flexibility and controllable data-rate granularity.

With conventional Quadrature Phase Shift Keying (QPSK), to achieve maximum spectral efficiency, we need high spectral efficient Nyquist filters which takes high FPGA resources for digital signal processing (DSP). Hence, we investigated Quadrature Duobinary (QDB) modulation as a solution to reduce the FPGA resources required for DSP while achieving spectral efficiency of 2bits/s/Hz. Currently we are investigating all analog single sideband (SSB) complex field modulated direct detection system. Here, we are trying to achieve higher spectral efficiency by using QDB modulation scheme in comparison to QPSK while avoiding signal-signal beat interference (SSBI) by providing a guard-band based approach.

Another topic we investigated, both through simulation and experiments, is a way to compensate for nonlinearities generated by semiconductor optical amplifiers (SOA) when operated in gain saturation in a field modulated direct detection systems. We successfully, compensated for the SOA nonlinearities in the presence of fiber chromatic dispersion, which was post compensated using electronic dispersion compensation after restoring the phase information of the received signal using Kramers-Kronig receiver.


Theresa Moore

Array Manifold Calibration for Multichannel SAR Sounders

When & Where:


Zoom Meeting, please contact jgrisafe@ku.edu for link

Committee Members:

James Stiles, Chair
John Paden (Co-Chair)
Shannon Blunt
Carl Leuschen
Leigh Stearns

Abstract

Multichannel synthetic aperture radar (SAR) sounders with cross-track antenna arrays map ice sheet basal morphology in three dimensions with a single pass using tomography.  The tomographic ice-sheet imaging method leverages parametric direction-finding techniques like the Maximum Likelihood Estimator and the Multiple Signal Classification algorithm to resolve scattering interfaces in elevation.  These techniques have received considerable attention because of their potential to exceed the Rayleigh resolution limit of the receive array under certain conditions.  This performance is predicated on having perfect knowledge of the frequency-dependent response of the array to directional sources, referred to as the array manifold.  Even modest amounts of mismatch between the assumed and actual manifold model degrade the accuracy of parametric angle estimators and erode their sought-after superresolution potential.

 

Array manifold calibration refers to the step in the array processor of refining our representation of the directional array-response vectors by accounting for factors such as mutual coupling, geometric uncertainties, and channel-to-channel gain imbalances.  Pilot calibration requires measuring the in-situ array over its field of view and storing the manifold in a look-up-table.  Alternatively, the array transfer function may be modeled parametrically to levy an estimation framework for characterizing mismatch.  Parametric calibration theory for sensor position perturbations has been established for several decades.  However, there remains a marked disconnect between the signal processing and antennas communities regarding how to include mutual coupling within the parametric framework.  To date, literature lacks validated studies that address parameterization of the embedded element patterns for direction-finding arrays.

 

A manifold calibration methodology is proposed for an airborne, multichannel ice-penetrating SAR.  The methodology departs from conventional approaches by extracting calibration targets from SAR imagery of well-understood terrain to empirically characterize the directional responses of the integrated array's embedded element patterns.  This work presents a Maximum Likelihood Estimator for nonlinear parameters common across disjoint calibration sets that has the potential to improve the accuracy of our estimated geometric uncertainties by increasing the total Fisher information in our observations.  The investigation contributes to specific gaps in array signal processing and remote sensing literature by treating the unique challenge of calibrating in-situ arrays used in direction-finding applications.


Dung Viet Nguyen

Particle Swarm Deep Reinforcement Learning for Base Station Optimization in Urban Areas

When & Where:


Zoom Meeting, please contact jgrisafe@ku.edu for link

Committee Members:

Taejoon Kim, Chair
Morteza Hashemi
Heechul Yun


Abstract

Densifying the network by deploying many small cells has attracted significant interests from wireless industries for exploring its potential to facilitating the proposed many data-intensive use cases in fifth-generation (5G) networks. While such efforts are essential, there are gaps in fundamental research and practical deployment of small cells. It is clear that increased interference from adjacent cells, called intercell interference, is the major limiting factor.  In order to address this issue, each base station's parameters should be properly controlled to mitigate the intercell interference. We call the task of designing the base station's parameters the base station optimization (BSO) problem in this work. Due to the large numbers of small cells and mobile users distributed over the network, solving BSO by precisely modeling the network conditions is almost infeasible. One of the popular approaches that has attracted many researchers recently is a data-based framework called machine learning (ML). While supervised ML is prevalent, it requires pre-labeled off-line data that are not available in many wireless scenarios. Unlike supervised ML, reinforcement learning (RL) can handle this situation because it is based on designing a good policy to find the best exploration-\&-exploitation tradeoff without the pre-labeled training dataset. Thus, in this work, we present a new approach to the problem of BSO, based on the application of deep reinforcement learning (DRL) to enhance the quality of service (QoS) experienced by mobile users. To speed up the exploration of DRL, we employ particle swarm optimization (PSO), which shows improved QoS and convergence compared to conventional DRL.


Dalton Hahn

Delving Into DevOps: Examining the Security Posture of State-of-Art Service Mesh Tools

When & Where:


Zoom Meeting, please contact jgrisafe@ku.edu for link

Committee Members:

Alex Bardas, Chair
Drew Davidson
Fengjun Li


Abstract

Explosion in the use of containers and a shift in software engineering design from monolithic applications into a microservice model has driven a need for software solutions that can manage the deployment and networking of microservices at enterprise-level scale. Service meshes have emerged as a promising solution to the microservice eruption that enterprise software is currently experiencing. This work examines service meshes from the perspective of security solutions offered within the tools and how the available security mechanisms impact the original goals of service meshes. As part of this study, we propose a relevant threat model to the service mesh domain and consider two different levels of configuration of these tools. The first configuration we study is the “idealized” configuration; one in which a system administrator has deep knowledge and the ability to properly configure and enable all available security mechanisms within a service mesh. The second configuration scenario is that of the default configuration deployment of service meshes. Through this work, we consider a range of adversarial approaches and scenarios that comprehensively cover the available attack surface of service meshes. Our experimental results show a distinct lack in security support of service meshes when deployed under default configurations, and additionally, in many idealized scenarios studied, it is possible for attackers to achieve some of their adversarial goals, presenting tempting targets to attackers.


Calen Carabajal

Development of Compact UWB Transmit Receive Modules and Filters on Liquid Crystal Polymer for Radar

When & Where:


Zoom Meeting, please contact jgrisafe@ku.edu for link

Committee Members:

Carl Leuschen, Chair
Fernando Rodriguez-Morales (Co-Chair)
Christopher Allen


Abstract

Microwave and mm-wave radars have been used extensively for remote sensing applications, and ultra-wideband (UWB) radars have provided particular utility in geophysical research due to their ability to resolve narrowly-spaced targets or media interface levels. With increased availability of unmanned aerial vehicles (UAS) and expanded application of microwave radars into other realms requiring portability, miniaturization of radar systems is a crucial goal. This thesis presents the design and development of various microwave components for a compact, airborne snow-probing radar with multi-gigahertz bandwidth and cm-scale vertical resolution.

 
First, a set of UWB, compact transmit and receive modules with custom power sequencing circuits is presented. These modules were rapid-prototyped as an initial step toward the miniaturization of the radar’s front-end, using a combination of custom and COTS circuits. The transmitter and receiver modules operate in the 2–18 GHz range. Laboratory and field tests are discussed, demonstrating performance that is comparable to previous, connectorized implementations of the system, while accomplishing a 5:1 size reduction.

 

Next, a set of miniaturized band-pass and low-pass filters is developed and demonstrated. This work addressed the lack of COTS circuits with adequate performance in a sufficiently small form factor that is compatible with the planar integration required in a multi-chip module.

 

The filters presented here were designed for manufacture on a multi-layer liquid crystal polymer (LCP) substrate. A detailed trade study to assess the effects of potential manufacturing tolerances is presented. A framework for the automated creation of panelized design variations was developed using CAD tools. Thirty-two design variations with two different types of launches (microstrip and grounded co-planar waveguide) were successfully simulated, fabricated and tested, showing good electrical performance both as individual filters and cascaded to offer outstanding out-of-band rejection. The size of the new filters is 1 cm x 1 cm x 150 µm, a vertical reduction of over 90% and a reduction of total cascaded length by over 80%.


Kunal Karnik

Augment drone GPS telemetry data onto its Optical Flow lines

When & Where:


Zoom Meeting, please contact jgrisafe@ku.edu for link

Committee Members:

Andy Gill, Chair
Drew Davidson
Prasad Kulkarni


Abstract

Optical flow is the apparent displacement of objects, surfaces and edges in a visual scene caused because of the relative motion between an observer and the scene. This apparent displacement (parallax) is used to render optical flow lines for such objects which hold invaluable information about their motion. In this research, we apply this technique to study a video file. We will locate pixels of objects with strong optical flow displacements. Which will enable us to identify an aerial multirotor craft (drone) from possible object pixels. Further we will not only mark the drones path using optical flow lines, but we will also add value to the video file by augmenting the drone’s 3D Telemetry data onto its optical flow lines.


Guojun Xiong

Distributed Filter Design and Power Allocation for Small-Cell MIMO Network

When & Where:


Zoom Meeting, please contact jgrisafe@ku.edu for link

Committee Members:

Taejoon Kim, Chair
Morteza Hashemi
Erik Perrins


Abstract

The deluge of wireless data traffic catalyzed by the growing number of data-intensive devices has motivated the deployment of small-cell in fifth-generation (5G) networks. A primary challenge for deploying dense small-cell networks comes from the lack of practical techniques that efficiently handle the increased network interference at a low cost. This has aroused considerable interest in the distributed precoder/combiner coordination techniques that leverage the channel reciprocity, while relying on the local channel state information (CSI) available at each communication end. In this project, a distributed approach is proposed to the problem of signal-to-interference-plus-noise-ratio (SINR)-guaranteed power minimization (SGPM) for multicell multiuser (MCMU) multiple-input multiple-output (MIMO) systems. Unlike prior SGPM approaches, the technique is based on solving necessary and sufficient optimality conditions, which are derived by decomposing the original problem into forward and backward (FB) subproblems, while ensuring the strong duality of each subproblems. The proposed distributed SGPM algorithm makes use of FB adaptation and Jacobi recursion for iterative filter design and power allocation, respectively, which guarantees target SINR performance as well as its convergence to a stationary point. Simulation results illustrate the enhanced power efficiency with the performance guarantees of the proposed method compared to the existing distributed techniques.


Jason Baxter

An FPGA Implementation of Carrier Phase and Symbol Timing Synchronization for 16-APSK

When & Where:


Zoom Meeting, please contact jgrisafe@ku.edu for link

Committee Members:

Erik Perrins, Chair
Taejoon Kim
Carl Leuschen


Abstract

Proper synchronization between a transmitter and receiver, in terms of carrier phase and symbol timing, is critical for reliable communication. Carrier phase synchronization is related to the frequency translation hardware, where perfect synchronization means that the local oscillators of the transmitter’s upconverter and receiver’s downconverter are aligned in phase and frequency. Timing synchronization is related to the analog-to-digital converter in the receiver, where perfect synchronization means that samples of the received signal are taken at transmitted symbol times. Perfect synchronization is unlikely in practical systems for a number of reasons, including hardware limitations and the independence of the transmitter and receiver. This thesis explores an FPGA implementation of a PLL-based carrier phase and symbol timing synchronization subsystem as part of a 16-APSK aeronautical telemetry receiver. The theory behind this subsystem is presented, and the hardware implementation of each component is described. Results demonstrate successful demodulation of a test signal, and system performance is shown to be comparable to double-precision floating point simulations in terms of error vector magnitude, synchronization lock time, and BER.


Adam Petz

An Infrastructure for Faithful Execution of Remote Attestation Protocols

When & Where:


Zoom Meeting, please contact jgrisafe@ku.edu for link

Committee Members:

Perry Alexander, Chair
Drew Davidson
Andy Gill
Prasad Kulkarni
Emily Witt

Abstract

Security decisions often rely on trust.  An emerging technology for gaining trust in a remote computing system is remote attestation.  Remote attestation is the activity of making a claim about properties of a target by supplying evidence to an appraiser over a network.  Although many existing approaches to remote attestation wisely adopt a layered architecture–where the bottom layers measure layers above–the dependencies between components remain static and measurement orderings fixed.  Further, they are often restricted to a specialized embedded platform, or only perform shallow measurements on a component of interest without considering the trustworthiness of its context or the attestation mechanism itself.  For modern computing environments with diverse topologies, we can no longer fix a target architecture any more than we can fix a protocol to measure that architecture.

Copland is a domain-specific language and formal framework that provides a vocabulary for specifying the goals of layered attestation protocols.  It remains configurable by measurement capability, participants, and platform topology, yet provides a precise reference semantics that characterizes system measurement events and evidence handling; a foundation for comparing protocol alternatives.  The aim of this work is to refine the Copland semantics to a more fine-grained notion of attestation manager execution–a high-privilege thread of control responsible for invoking attestation services and bundling evidence results.  This refinement consists of two cooperating components called the Copland Compiler and the Attestation Virtual Machine (AVM).  The Copland Compiler translates a Copland specification into a sequence of primitive attestation instructions to be executed in the AVM.  These components are implemented as functional programs in the Coq proof assistant and proved correct with respect to the Copland reference semantics.  This formal connection is critical in order to trust that protocol specifications are faithfully carried out by the attestation manger implementation.  We also explore synthesis of appraisal routines that leverage the same formally verified infrastructure to interpret evidence generated by Copland protocols and make trust decisions.