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Description
Eigenvalues of the Gram matrix formed from received data frequently appear in sufficient detection statistics for multi-channel detection with Generalized Likelihood Ratio (GLRT) and Bayesian tests. In a frequently presented model for passive radar, in which the null hypothesis is that the channels are independent and contain only complex white Gaussian noise and the alternative hypothesis is that the channels contain a common rank-one signal in the mean, the GLRT statistic is the largest eigenvalue $\lambda_1$ of the Gram matrix formed from data. This Gram matrix has a Wishart distribution. Although exact expressions for the distribution of $\lambda_1$ are known under both hypotheses, numerically calculating values of these distribution functions presents difficulties in cases where the dimension of the data vectors is large. This dissertation presents tractable methods for computing the distribution of $\lambda_1$ under both the null and alternative hypotheses through a technique of expanding known expressions for the distribution of $\lambda_1$ as inner products of orthogonal polynomials. These newly presented expressions for the distribution allow for computation of detection thresholds and receiver operating characteristic curves to arbitrary precision in floating point arithmetic. This represents a significant advancement over the state of the art in a problem that could previously only be addressed by Monte Carlo methods.
ContributorsJones, Scott, Ph.D (Author) / Cochran, Douglas (Thesis advisor) / Berisha, Visar (Committee member) / Bliss, Daniel (Committee member) / Kosut, Oliver (Committee member) / Richmond, Christ (Committee member) / Arizona State University (Publisher)
Created2019
Description
This dissertation studies two outstanding microscale fluid mechanics problems: 1) mechanisms of gas production from the nanopores of shale; 2) enhanced mass flow rate in steady compressible gas flow through a micro-conduit.
The dissertation starts with a study of a volumetric expansion driven drainage flow of a viscous compressible fluid from a small capillary and channel in the low Mach number limit. An analysis based on the linearized compressible Navier-Stokes equations with no-slip condition shows that fluid drainage is controlled by the slow decay of the acoustic wave inside the capillary and the no-slip flow exhibits a slip-like mass flow rate. Numerical simulations are also carried out for drainage from a small capillary to a reservoir or a contraction of finite size. By allowing the density wave to escape the capillary, two wave leakage mechanisms are identified, which are dependent on the capillary length to radius ratio, reservoir size and acoustic Reynolds number. Empirical functions are generated for an effective diffusive coefficient which allows simple calculations of the drainage rate using a diffusion model without the presence of the reservoir or contraction.
In the second part of the dissertation, steady viscous compressible flow through a micro-conduit is studied using compressible Navier-Stokes equations with no-slip condition. The mathematical theory of Klainerman and Majda for low Mach number flow is employed to derive asymptotic equations in the limit of small Mach number. The overall flow, a combination of the Hagen-Poiseuille flow and a diffusive velocity shows a slip-like mass flow rate even through the overall velocity satisfies the no-slip condition. The result indicates that the classical formulation includes self-diffusion effect and it embeds the Extended Navier-Stokes equation theory (ENSE) without the need of introducing additional constitutive hypothesis or assuming slip on the boundary. Contrary to most ENSE publications, the predicted mass flow rate is still significantly below the measured data based on an extensive comparison with thirty-five experiments.
The dissertation starts with a study of a volumetric expansion driven drainage flow of a viscous compressible fluid from a small capillary and channel in the low Mach number limit. An analysis based on the linearized compressible Navier-Stokes equations with no-slip condition shows that fluid drainage is controlled by the slow decay of the acoustic wave inside the capillary and the no-slip flow exhibits a slip-like mass flow rate. Numerical simulations are also carried out for drainage from a small capillary to a reservoir or a contraction of finite size. By allowing the density wave to escape the capillary, two wave leakage mechanisms are identified, which are dependent on the capillary length to radius ratio, reservoir size and acoustic Reynolds number. Empirical functions are generated for an effective diffusive coefficient which allows simple calculations of the drainage rate using a diffusion model without the presence of the reservoir or contraction.
In the second part of the dissertation, steady viscous compressible flow through a micro-conduit is studied using compressible Navier-Stokes equations with no-slip condition. The mathematical theory of Klainerman and Majda for low Mach number flow is employed to derive asymptotic equations in the limit of small Mach number. The overall flow, a combination of the Hagen-Poiseuille flow and a diffusive velocity shows a slip-like mass flow rate even through the overall velocity satisfies the no-slip condition. The result indicates that the classical formulation includes self-diffusion effect and it embeds the Extended Navier-Stokes equation theory (ENSE) without the need of introducing additional constitutive hypothesis or assuming slip on the boundary. Contrary to most ENSE publications, the predicted mass flow rate is still significantly below the measured data based on an extensive comparison with thirty-five experiments.
ContributorsShen, Di (Author) / Chen, Kangping (Thesis advisor) / Herrmann, Marcus (Committee member) / Huang, Huei-Ping (Committee member) / Calhoun, Ronald (Committee member) / Lopez, Juan (Committee member) / Arizona State University (Publisher)
Created2019
Description
A wideband hybrid envelope tracking modulator utilizing a hysteretic-controlled three-level switching converter and a slew-rate enhanced linear amplifierer is presented. In addition to smaller ripple and lower losses of three-level switching converters, employing the proposed hysteresis control loop results in a higher speed loop and wider bandwidth converter, enabling over 80MHz of switching frequency. A concurrent sensor circuit monitors and regulates the flying capacitor voltage VCF and eliminates conventional required calibration loop to control it. The hysteretic-controlled three-level switching converter provides a high percentage of power amplifier supply load current with lower ripple, reducing the linear amplifier high-frequency current and ripple cancellation current, improving the overall system efficiency. A slew-rate enhancement (SRE) circuit is employed in the linear amplifier resulting in slew-rate of
over 307V/us and bandwidth of over 275MHz for the linear amplifier. The slew-rate enhancement circuit provides a parallel auxiliary current path directly to the gate of the class-AB output stage transistors, speeding-up the charging or discharging of out-
put without modifying the operating point of the remaining linear amplifier, while maintaining the quiescent current of the class-AB stage. The supply modulator is fabricated in 65nm CMOS process. The measurement results show the tracking of LTE-40MHz envelope with 93% peak efficiency at 1W output power, while the SRE is disabled. Enabling the SRE it can track LTE-80MHz envelope with peak efficiency of 91%.
over 307V/us and bandwidth of over 275MHz for the linear amplifier. The slew-rate enhancement circuit provides a parallel auxiliary current path directly to the gate of the class-AB output stage transistors, speeding-up the charging or discharging of out-
put without modifying the operating point of the remaining linear amplifier, while maintaining the quiescent current of the class-AB stage. The supply modulator is fabricated in 65nm CMOS process. The measurement results show the tracking of LTE-40MHz envelope with 93% peak efficiency at 1W output power, while the SRE is disabled. Enabling the SRE it can track LTE-80MHz envelope with peak efficiency of 91%.
ContributorsMahmoudidaryan, Parisa (Author) / Kiaei, Sayfe (Thesis advisor) / Bakkaloglu, Bertan (Committee member) / Kitchen, Jennifer (Committee member) / Mehdizad Taleie, Shahin (Committee member) / Arizona State University (Publisher)
Created2019
Description
Background – Among influential education reports, there is clear consensus that an expansive range of intrapersonal (e.g. self-regulation) and interpersonal competencies (e.g. empathy) highly influence educational and career success. Research on teaching and learning these competencies is limited in engineering education.
Purpose/Hypothesis – This dissertation study explores the impacts of a mindfulness training program on first-year engineering students and aims to understand potential impacts on the development of intrapersonal and interpersonal competencies.
Design/Method – A four-session mindfulness-based training program was designed, developed, and facilitated to cultivate intrapersonal and interpersonal competencies. This study employed a multiphase mixed method design in which quantitative and qualitative data was collected from a total of 35 different students through a post survey (n=31), 3-month follow-up survey (n=29), and interviews (n=18). t-tests were used to evaluate the statistical significance of the program and a rigorous thematic analysis process was utilized to help explain the quantitative data.
Results – The results suggest that the majority of students became more mindful, which led to improved intrapersonal competencies (i.e. self-management, critical-thinking, focus, resilience, and well-being) and interpersonal competencies (i.e. empathy, communication, teamwork, and leadership).
Discussion / Conclusions – The study provides compelling evidence that mindfulness training can support the development of intrapersonal and interpersonal skills among engineering students, which can support their overall academic experience, as well as personal and professional development. Future design and development work will be needed to evaluate the integration and scalability potential of mindfulness training within engineering programs.
Purpose/Hypothesis – This dissertation study explores the impacts of a mindfulness training program on first-year engineering students and aims to understand potential impacts on the development of intrapersonal and interpersonal competencies.
Design/Method – A four-session mindfulness-based training program was designed, developed, and facilitated to cultivate intrapersonal and interpersonal competencies. This study employed a multiphase mixed method design in which quantitative and qualitative data was collected from a total of 35 different students through a post survey (n=31), 3-month follow-up survey (n=29), and interviews (n=18). t-tests were used to evaluate the statistical significance of the program and a rigorous thematic analysis process was utilized to help explain the quantitative data.
Results – The results suggest that the majority of students became more mindful, which led to improved intrapersonal competencies (i.e. self-management, critical-thinking, focus, resilience, and well-being) and interpersonal competencies (i.e. empathy, communication, teamwork, and leadership).
Discussion / Conclusions – The study provides compelling evidence that mindfulness training can support the development of intrapersonal and interpersonal skills among engineering students, which can support their overall academic experience, as well as personal and professional development. Future design and development work will be needed to evaluate the integration and scalability potential of mindfulness training within engineering programs.
ContributorsHuerta, Mark Vincent (Author) / McKenna, Anna (Thesis advisor) / Pipe, Teri (Committee member) / Carberry, Adam (Committee member) / Arizona State University (Publisher)
Created2019
Description
Vehicles traverse granular media through complex reactions with large numbers of small particles. Many approaches rely on empirical trends derived from wheeled vehicles in well-characterized media. However, the environments of numerous bodies such as Mars or the moon are primarily composed of fines called regolith which require different design considerations. This dissertation discusses research aimed at understanding the role and function of empirical, computational, and theoretical granular physics approaches as they apply to helical geometries, their envelope of applicability, and the development of new laws. First, a static Archimedes screw submerged in granular material (glass beads) is analyzed using two methods: Granular Resistive Force Theory (RFT), an empirically derived set of equations based on fluid dynamic superposition principles, and Discrete element method (DEM) simulations, a particle modeling software. Dynamic experiments further confirm the computational method with multi-body dynamics (MBD)-DEM co-simulations. Granular Scaling Laws (GSL), a set of physics relationships based on non-dimensional analysis, are utilized for the gravity-modified environments. A testing chamber to contain a lunar analogue, BP-1, is developed and built. An investigation of straight and helical grousered wheels in both silica sand and BP-1 is performed to examine general GSL applicability for lunar purposes. Mechanical power draw and velocity prediction by GSL show non-trivial but predictable deviation. BP-1 properties are characterized and applied to an MBD-DEM environment for the first time. MBD-DEM simulation results between Earth gravity and lunar gravity show good agreement with theoretical predictions for both power and velocity. The experimental deviation is further investigated and found to have a mass-dependant component driven by granular sinkage and engagement. Finally, a robust set of helical granular scaling laws (HGSL) are derived. The granular dynamics scaling of three-dimensional screw-driven mobility is reduced to a similar theory as wheeled scaling laws, provided the screw is radially continuous. The new laws are validated in BP-1 with results showing very close agreement to predictions. A gravity-variant version of these laws is validated with MBD-DEM simulations. The results of the dissertation suggest GSL, HGSL, and MBD-DEM give reasonable approximations for use in lunar environments to predict rover mobility given adequate granular engagement.
ContributorsThoesen, Andrew Lawrence (Author) / Marvi, Hamidreza (Thesis advisor) / Berman, Spring (Committee member) / Emady, Heather (Committee member) / Lee, Hyunglae (Committee member) / Klesh, Andrew (Committee member) / Arizona State University (Publisher)
Created2019
Description
This thesis presents efficient implementations of several linear algebra kernels, machine learning kernels and a neural network based recommender systems engine onto a massively parallel reconfigurable architecture, Transformer. The linear algebra kernels include Triangular Matrix Solver (TRSM), LU Decomposition (LUD), QR Decomposition (QRD), and Matrix Inversion. The machine learning kernels include an LSTM (Long Short Term Memory) cell, and a GRU (gated Recurrent Unit) cell used in recurrent neural networks. The neural network based recommender systems engine consists of multiple kernels including fully connected layers, embedding layer, 1-D batchnorm, Adam optimizer, etc.
Transformer is a massively parallel reconfigurable multicore architecture designed at the University of Michigan. The Transformer configuration considered here is 4 tiles and 16 General Processing Elements (GPEs) per tile. It supports a two level cache hierarchy where the L1 and L2 caches can operate in shared (S) or private (P) modes. The architecture was modeled using Gem5 and cycle accurate simulations were done to evaluate the performance in terms of execution times, giga-operations per second per Watt (GOPS/W), and giga-floating-point-operations per second per Watt (GFLOPS/W).
This thesis shows that for linear algebra kernels, each kernel achieves high performance for a certain cache mode and that this cache mode can change when the matrix size changes. For instance, for smaller matrix sizes, L1P, L2P cache mode is best for TRSM, while L1S, L2S is the best cache mode for LUD, and L1P, L2S is the best for QRD. For each kernel, the optimal cache mode changes when the matrix size is increased. For instance, for TRSM, the L1P, L2P cache mode is best for smaller matrix sizes ($N=64, 128, 256, 512$) and it changes to L1S, L2P for larger matrix sizes ($N=1024$). For machine learning kernels, L1P, L2P is the best cache mode for all network parameter sizes.
Gem5 simulations show that the peak performance for TRSM, LUD, QRD and Matrix Inverse in the 14nm node is 97.5, 59.4, 133.0 and 83.05 GFLOPS/W, respectively. For LSTM and GRU, the peak performance is 44.06 and 69.3 GFLOPS/W.
The neural network based recommender system was implemented in L1S, L2S cache mode. It includes a forward pass and a backward pass and is significantly more complex in terms of both computational complexity and data movement. The most computationally intensive block is the fully connected layer followed by Adam optimizer. The overall performance of the recommender systems engine is 54.55 GFLOPS/W and 169.12 GOPS/W.
Transformer is a massively parallel reconfigurable multicore architecture designed at the University of Michigan. The Transformer configuration considered here is 4 tiles and 16 General Processing Elements (GPEs) per tile. It supports a two level cache hierarchy where the L1 and L2 caches can operate in shared (S) or private (P) modes. The architecture was modeled using Gem5 and cycle accurate simulations were done to evaluate the performance in terms of execution times, giga-operations per second per Watt (GOPS/W), and giga-floating-point-operations per second per Watt (GFLOPS/W).
This thesis shows that for linear algebra kernels, each kernel achieves high performance for a certain cache mode and that this cache mode can change when the matrix size changes. For instance, for smaller matrix sizes, L1P, L2P cache mode is best for TRSM, while L1S, L2S is the best cache mode for LUD, and L1P, L2S is the best for QRD. For each kernel, the optimal cache mode changes when the matrix size is increased. For instance, for TRSM, the L1P, L2P cache mode is best for smaller matrix sizes ($N=64, 128, 256, 512$) and it changes to L1S, L2P for larger matrix sizes ($N=1024$). For machine learning kernels, L1P, L2P is the best cache mode for all network parameter sizes.
Gem5 simulations show that the peak performance for TRSM, LUD, QRD and Matrix Inverse in the 14nm node is 97.5, 59.4, 133.0 and 83.05 GFLOPS/W, respectively. For LSTM and GRU, the peak performance is 44.06 and 69.3 GFLOPS/W.
The neural network based recommender system was implemented in L1S, L2S cache mode. It includes a forward pass and a backward pass and is significantly more complex in terms of both computational complexity and data movement. The most computationally intensive block is the fully connected layer followed by Adam optimizer. The overall performance of the recommender systems engine is 54.55 GFLOPS/W and 169.12 GOPS/W.
ContributorsSoorishetty, Anuraag (Author) / Chakrabarti, Chaitali (Thesis advisor) / Kim, Hun Seok (Committee member) / LiKamWa, Robert (Committee member) / Arizona State University (Publisher)
Created2019
Description
Power management integrated circuit (PMIC) design is a key module in almost all electronics around us such as Phones, Tablets, Computers, Laptop, Electric vehicles, etc. The on-chip loads such as microprocessors cores, memories, Analog/RF, etc. requires multiple supply voltage domains. Providing these supply voltages from off-chip voltage regulators will increase the overall system cost and limits the performance due to the board and package parasitics. Therefore, an on-chip fully integrated voltage regulator (FIVR) is required.
The dissertation presents a topology for a fully integrated power stage in a DC-DC buck converter achieving a high-power density and a time-domain hysteresis based highly integrated buck converter. A multi-phase time-domain comparator is proposed in this work for implementing the hysteresis control, thereby achieving a process scaling friendly highly digital design. A higher-order LC notch filter along with a flying capacitor which couples the input and output voltage ripple is implemented. The power stage operates at 500 MHz and can deliver a maximum power of 1.0 W and load current of 1.67 A, while occupying 1.21 mm2 active die area. Thus achieving a power density of 0.867 W/mm2 and current density of 1.377 A/mm2. The peak efficiency obtained is 71% at 780 mA of load current. The power stage with the additional off-chip LC is utilized to design a highly integrated current mode hysteretic buck converter operating at 180 MHz. It achieves 20 ns of settling and 2-5 ns of rise/fall time for reference tracking.
The second part of the dissertation discusses an integrated low voltage switched-capacitor based power sensor, to measure the output power of a DC-DC boost converter. This approach results in a lower complexity, area, power consumption, and a lower component count for the overall PV MPPT system. Designed in a 180 nm CMOS process, the circuit can operate with a supply voltage of 1.8 V. It achieves a power sense accuracy of 7.6%, occupies a die area of 0.0519 mm2, and consumes 0.748 mW of power.
The dissertation presents a topology for a fully integrated power stage in a DC-DC buck converter achieving a high-power density and a time-domain hysteresis based highly integrated buck converter. A multi-phase time-domain comparator is proposed in this work for implementing the hysteresis control, thereby achieving a process scaling friendly highly digital design. A higher-order LC notch filter along with a flying capacitor which couples the input and output voltage ripple is implemented. The power stage operates at 500 MHz and can deliver a maximum power of 1.0 W and load current of 1.67 A, while occupying 1.21 mm2 active die area. Thus achieving a power density of 0.867 W/mm2 and current density of 1.377 A/mm2. The peak efficiency obtained is 71% at 780 mA of load current. The power stage with the additional off-chip LC is utilized to design a highly integrated current mode hysteretic buck converter operating at 180 MHz. It achieves 20 ns of settling and 2-5 ns of rise/fall time for reference tracking.
The second part of the dissertation discusses an integrated low voltage switched-capacitor based power sensor, to measure the output power of a DC-DC boost converter. This approach results in a lower complexity, area, power consumption, and a lower component count for the overall PV MPPT system. Designed in a 180 nm CMOS process, the circuit can operate with a supply voltage of 1.8 V. It achieves a power sense accuracy of 7.6%, occupies a die area of 0.0519 mm2, and consumes 0.748 mW of power.
ContributorsSingh, Shrikant (Author) / Kiaei, Sayfe (Thesis advisor) / Bakkaloglu, Bertan (Thesis advisor) / Kitchen, Jennifer (Committee member) / Song, Hongjiang (Committee member) / Arizona State University (Publisher)
Created2019
Description
The availability of bulk gallium nitride (GaN) substrates has generated great interest in the development of vertical GaN-on-GaN power devices. The vertical devices made of GaN have not been able to reach their true potential due to material growth related issues. Power devices typically have patterned p-n, and p-i junctions in lateral, and vertical direction relative to the substrate. Identifying the variations from the intended layer design is crucial for failure analysis of the devices. A most commonly used dopant profiling technique, secondary ion mass spectroscopy (SIMS), does not have the spatial resolution to identify the dopant distribution in patterned devices. The possibility of quantitative dopant profiling at a sub-micron scale for GaN in a scanning electron microscope (SEM) is discussed. The total electron yield in an SEM is shown to be a function of dopant concentration which can potentially be used for quantitative dopant profiling.
Etch-and-regrowth is a commonly employed strategy to generate the desired patterned p-n and p-i junctions. The devices involving etch-and-regrowth have poor performance characteristics like high leakage currents, and lower breakdown voltages. This is due to damage induced by the dry etching process, and the nature of the regrowth interface, which is important to understand in order to address the key issue of leakage currents in etched and regrown devices. Electron holography is used for electrostatic potential profiling across the regrowth interfaces to identify the charges introduced by the etching process. SIMS is used to identify the impurities introduced at the interfaces due to etch-and-regrowth process.
Etch-and-regrowth is a commonly employed strategy to generate the desired patterned p-n and p-i junctions. The devices involving etch-and-regrowth have poor performance characteristics like high leakage currents, and lower breakdown voltages. This is due to damage induced by the dry etching process, and the nature of the regrowth interface, which is important to understand in order to address the key issue of leakage currents in etched and regrown devices. Electron holography is used for electrostatic potential profiling across the regrowth interfaces to identify the charges introduced by the etching process. SIMS is used to identify the impurities introduced at the interfaces due to etch-and-regrowth process.
ContributorsAlugubelli, Shanthan Reddy (Author) / Ponce, Fernando A. (Thesis advisor) / McCartney, Martha (Committee member) / Newman, Nathan (Committee member) / Zhao, Yuji (Committee member) / Arizona State University (Publisher)
Created2019
Description
Silicon photovoltaics is the dominant contribution to the global solar energy production. As increasing conversion efficiency has become one of the most important factors to lower the cost of photovoltaic systems, the idea of making a multijunction solar cell based on a silicon bottom cell has attracted broad interest. Here the potential of using dilute nitride GaNPAs alloys for a lattice-matched 3-terminal 2-junction Si-based tandem solar cell through multiscale modeling is investigated. To calculate the electronic band structure of dilute nitride alloys with relatively low computational cost, the sp^3 d^5 s^* s_N tight-binding model is chosen, as it has been demonstrated to obtain quantitatively correct trends for the lowest conduction band near Γ, L, and X for dilute-N GaNAs. A genetic algorithm is used to optimize the sp^3 d^5 s^* tight-binding model for pure GaP and GaAs for their optical properties. Then the optimized sp^3 d^5 s^* s_N parametrizations are obtained for GaNP and GaNAs by fitting to experimental bandgap values. After that, a virtual crystal approach gives the Hamiltonian for GaNPAs alloys. From their tight-binding Hamiltonian, the first-order optical response functions of dilute nitride GaNAs, GaNP, and GaNPAs are calculated. As the N mole fraction varies, the calculated critical optical features vary with the correct trends, and agree well with experiment. The calculated optical properties are then used as input for the solar device simulations based on Silvaco ATLAS. For device simulation, a bottom cell model is first constructed to generate performance results that agree well with a demonstrated high-efficiency Si heterojunction interdigitated back contact (IBC) solar cell reported by Kaneka. The front a-Si/c-Si interface is then replaced by a GaP/Si interface for the investigation of the sensitivity of the GaP/Si interface to interface defects in terms of degradation of the IBC cell performance, where we find that an electric field that induces strong band bending can significantly mitigate the impact of the interfacial traps. Finally, a lattice-matched 3-terminal 2-junction tandem model is built for performance simulation by stacking a dilute nitride GaNP(As) cell on the Si IBC cell connected through a GaP/Si interface. The two subcells operate quasi-independently. In this 3-terminal tandem model, traps at the GaP/Si interface still significantly impact the performance of the Si subcell, but their effects on the GaNP subcell are relatively small. Assuming the interfacial traps are well passivated, the tandem efficiency surpasses that of a single-junction Si cell, with values close to 33% based on realistic parameters.
ContributorsZou, Yongjie (Author) / Goodnick, Stephen M. (Thesis advisor) / Honsberg, C. (Christiana B.) (Committee member) / King, Richard R. (Committee member) / Vasileska, Dragica (Committee member) / Arizona State University (Publisher)
Created2019
Description
State-of-the-art automotive radars use multi-chip Frequency Modulated Continuous Wave (FMCW) radars to sense the environment around the car. FMCW radars are prone to interference as they operate over a narrow baseband bandwidth and use similar radio frequency (RF) chirps among them. Phase Modulated Continuous Wave radars (PMCW) are robust and insensitive to interference as they transmit signals over a wider bandwidth using spread spectrum technique. As more and more cars are equipped with FMCW radars illuminate the same environment, interference would soon become a serious issue. PMCW radars can be an effective solution to interference in the noisy FMCW radar environment. PMCW radars can be implemented in silicon as System-on-a-chip (SoC), suitable for Multiple-Input-Multiple-Output (MIMO) implementation and is highly programmable. PMCW radars do not require highly linear high frequency chirping oscillators thus reducing the size of the final solution.
This thesis aims to present a behavior model for this promising Digitally modulated radar (DMR) transceiver in Simulink/Matlab. The goal of this work is to create a model for the electronic system level framework that simulates the entire system with non-idealities. This model includes a Top Down Design methodology to understand the requirements of the individual modules’ performance and thus derive the specifications for implementing the real chip. Back annotation of the actual electrical modules’ performance to the model closes the design process loop. Using Simulink’s toolboxes, a passband and equivalent baseband model of the system is built for the transceiver with non-idealities of the components built in along with signal processing routines in Matlab. This model provides a platform for system evaluation and simulation for various system scenarios and use-cases of sensing using the environment around a moving car.
This thesis aims to present a behavior model for this promising Digitally modulated radar (DMR) transceiver in Simulink/Matlab. The goal of this work is to create a model for the electronic system level framework that simulates the entire system with non-idealities. This model includes a Top Down Design methodology to understand the requirements of the individual modules’ performance and thus derive the specifications for implementing the real chip. Back annotation of the actual electrical modules’ performance to the model closes the design process loop. Using Simulink’s toolboxes, a passband and equivalent baseband model of the system is built for the transceiver with non-idealities of the components built in along with signal processing routines in Matlab. This model provides a platform for system evaluation and simulation for various system scenarios and use-cases of sensing using the environment around a moving car.
ContributorsKalyan, Prassana (Author) / Bakkaloglu, Bertan (Thesis advisor) / Kitchen, Jennifer (Thesis advisor) / Garrity, Douglas (Committee member) / Arizona State University (Publisher)
Created2019