M.Ing. (Electrical And Electronic Engineering) / A brief introduction to laser Doppler anemometry is given. Signal processing techniques for LOA are discussed with specific reference to the salient advantages and disadvantages of each. The abovementioned discussion motivates the use of adaptive filters as parametric spectral estimators for frequency ext~action from Doppler signals. Two adaptive algorithms ie. 'the least mean sqaures' (LMS) and the 'recursive least sqaures' (RLS), are discussed. Results of a real-time application of the LMS algorithm, as implemented on the TMS320-10, as well as the results from a full study of the Kalman algorithm are shown and discussed. The implementation of a digital signal processor to make the application of parametric spectral estimation to LOA viable is discussed under the following headings: analogue module; mathematical processor; communications module; storage an~ display unit. The system is based qn a eight bit converter with conversion rates ranging from the lower audio range to 20MHz. It has a versatile trigger system to facilitate easy capture of Doppler data. Captured data is stored in an onboard FIFO register and is available to the mathematical processing unit for spectral analysis. '/ The mathematical processing unit is a sixteen bit, multi-processor environment specifically implemented for parametric spectral estimation. The system comprises three TMS320-10 signal processors which are connected by means of a high speed parallel communications channel. Processed data is available to a display and storage system via a high speed interface card that interfaces the sixteen bit signal processor environment to the eight bit environment of the display device.

Synthetic Aperture Sonar (SAS) provides the best opportunity for side-looking sonar mounted on underwater platforms to achieve high-resolution images. However, SAS processing requires strict constraints on resolvable platform motion. The most common approach to estimate this motion is to use the Redundant Phase Center (RPC) technique. Here the ping interval is set, such that a portion of the sonar array overlaps as the sensor moves forward. The time delay between the pings received on these overlapping elements is estimated using cross-correlation. These time delays are then used to infer the pingto-ping vehicle motion. Given the stochastic nature of the operational environment, some level of decorrelation between these two signals is likely. In this research, two iterative signal decomposition methods well suited for nonlinear and non-stationary signals, are investigated for their potential to improve the Time Delay Estimation (TDE). The first of this type, the Empirical Mode Decomposition (EMD) was introduced by Huang in the seminal paper, The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis and is the foundation for the algorithms used in this research. This method decomposes a signal into a finite sequence of simple components termed Intrinsic Mode Functions (IMFs). The Iterative Filter (IF) approach, developed by Lin, Wang and Zhou, builds on the EMD framework. The sonar signals considered in this research are complex baseband signals. Both the IF and EMD algorithms were designed to decompose real signals. However, the IF variant, the Multivariate Fast Iterative Filtering (MFIF) Algorithm, developed by Cicone, and the EMD variant, the Fast and Adaptive Multivariate Empirical Mode Decomposition (FAMVEMD) algorithm, developed by Thirumalaisamy and Ansell, preserve both the magnitude and phase in the decomposition and hence were chosen for this analysis. / Includes bibliography. / Dissertation (Ph.D.)--Florida Atlantic University, 2021. / FAU Electronic Theses and Dissertations Collection

Oral communication has constituted as a necessary aspect of how people interact with one another, but there are always situations where this form of communication can create distractions, irritation, or even danger. Take for example, a student in a laboratory who needs to communicate effectively with a lab partner without creating a distraction to those trying to work around said student or a soldier on a battlefield who needs to relay information effectively to his or her comrades without revealing his or her position to the enemy. It becomes apparent that people need a more exclusive form of communication in order to ensure not only the safety of soldiers, but efficiency in the workplace as well. This project focuses on solving these problems by developing a small, concealable, and non-invasive, electronic device capable of transmitting communication silently by linking to a phone, computer, or radio channel. This device ensures completely silent communication between only those who use communicating devices and only requires that the user apply nodes to his or her throat when thinking of what he or she wishes to communicate with another for proper operation. Unlike other devices which rely on EEG and thus involve cumbersome headwear, this device performs as easily removable, concealable, hands free, conveniently pocket-sized, compatible with other devices used for communication, and able to have a user input versus device output accuracy of at least 70%. Using wavelet analysis and a MSP432 microcontroller, subvocal signals originating from the throat can be classified to an overall accuracy of at least 70% within a project budget of $50.

The problem of path planning occurs in many areas, such as computational biology, computer animations and computer-aided design. It is of particular importance in the field of robotics. Here, the task is to find a feasible path/trajectory that the robot can follow from a start to a goal configuration. For the basic path planning problem it is often assumed that a perfect model of the world surrounding the robot is known. In industrial robotics, such models are often based on, for example, CAD models. However, in applications of autonomous service robotics less knowledge about the environment is available. Efficient and robust path planning algorithms are here of major importance. To be truly autonomous, a robot should be able to plan all motions on its own. Furthermore, it has to be able to plan and re-plan in real time, which puts hard constraints on the acceptable computation time. This thesis presents a novel path planning method called Probabilistic Cell Decomposition (PCD). This approach combines the underlying method of cell decomposition with the concept of probabilistic sampling. The cell decomposition is iteratively refined until a collision-free path is found. In each immediate step the current cell decomposition is used to guide probabilistic sampling to important areas. The basic PCD algorithm can be decomposed into a number of components such as graph search, local planning, cell splitting and probabilistic sampling. For each component different approaches are discussed. The performance of PCD is then tested on a set of benchmark problems. The results are compared to those obtained by one of the most commonly used probabilistic path planning methods, namely Rapidly-exploring Random Trees. It is shown that PCD efficiently solves various kinds of path planning problems. Planning for autonomous manipulation often involves additional path constraints beyond collision avoidance. This thesis presents an application of PCD to path planning for a mobile manipulator. The robot has to fetch a carton of milk from the refrigerator and place it on the kitchen table. Here, opening the refrigerator involves motion with a pre-specified end-effector path. The results show that planning the different motions for the high-level task takes less time than actually executing them. The whole series of subtasks takes about 1.5 seconds to compute. / QC 20101209

<p>QCR 20161026</p>

Multiuser diversity can be used to significantly increase system throughput in wireless communication systems. The idea is to schedule users when they experience good channel conditions and let them wait when the channels are weak. In this thesis, several aspects on multiuser diversity OFDMA systems are investigated. An adaptive reduced feedback scheme for multiuser diversity OFDMA is proposed. It significantly reduces the total feedback overhead while maintaining a multiuser diversity gain. The scheme uses clusters of sub-carriers as feedback units and only feeds back information about the fading peaks. Furthermore, an opportunistic beamforming scheme for clustered OFDM is presented and evaluated. A key aspect of the opportunistic beamforming scheme is that it increases the frequency fading of users with relatively flat channels, which increases the likelihood of being scheduled. Scheduling is an important aspect of multiuser diversity. A modified proportional fair scheduler is proposed in this thesis. It incorporates user individual target bit-rates and delays and a tunable fairness level. These features makes the scheduler more attractive for future mixed service wireless systems. The use of the feedback information in the opportunistic beamforming process is discussed and evaluated. This extra information can help to increase the performance of unfairly treated users in the system. Several aspects of the proposed system are evaluated by means of simulation, using the 3GPP spatial channel model. In the simulations, the clustered beamforming performs better than three comparison systems. The modified proportional fair scheduler manages to divide the resources according to the user targets, while at the same time exploiting the multiuser diversity as well as the standard proportional fair algorithm. The thesis also includes results on coded packet error rate estimation from a channel realization by means of a two dimensional table. This can be useful in large network simulations as well as in designing adaptive modulation schemes.

No description available.

Pulse responses are not suitable for evaluating H(z) frequency responses that include digital errors. Digital error effects, however, are conveniently included in H(z) frequency response calculations based on the step response. A non-real time algorithm for computing the frequency response of a real time digital filters based on the filter step response is developed and verified through an example.

In this paper, the step modulated sine wave [u(t)Asin2πft] response of the low-pass, band-pass, and high-pass filters are evaluated. Butterworth filters from the first order on up to the ideal filter are analyzed, and expressions for the settle times developed. The longest settle time occurs for the ideal filter, with all other filters taking progressively less time to settle as the order decreases. A significant point is that the transient settle time for a filter depends on the difference in applied signal frequency and the filter cut off frequency. The set of expressions developed in this report are primarily intended to be sued in selecting programming time delays in computer based signal measurement and processing systems.

The hardware available for digital signal processing is evaluated. The elements required for implementation of digital signal processing applications are identified. These elements--memories, ALUs and multipliers -- are analyzed. Then the operation of parts which make up a range of possible solutions are evaluated. Thus, the graduating engineer is aided in making a transition from the theoretical to the practical world.