This master thesis investigates the problem of making an unmanned aerial vehicle(uav) follow a person or a group of persons while keeping a fixed distance tothe chosen target. The purpose of this thesis is to give a proof of concept prototypeof how such a system would work to achieve that task. The main problemconsists of controlling the uav based on visual input from a camera. With thehelp of a visual object detection and tracking system, the image coordinates ofthe targets can be found. An algorithm was developed to calculate the target’sworld position based on its image coordinates and the world position and orientationof the uav. A control system was implemented that uses that uses thepositional information to set the velocity of the uav, if its position needs to bechanged. Several strategies for handling groups of targets were investigated. Inaddition a simulator was developed that can be used to simulate the image coordinatesof a target when the world position of the target is known. The systemwas tested during live flights, using a high precision motion capture system forreference. The results were mainly positive in showing proof of concept and evenshowing a relatively high level of precision.

International Telemetering Conference Proceedings / October 25-28, 1999 / Riviera Hotel and Convention Center, Las Vegas, Nevada / Launch Vehicle tracking is indispensable due to the fact that wayward vehicles must be destroyed lest they cause loss of life and/or damage to property. Launch Vehicle tracking data is also useful in assessing vehicle performance and mission success. Cincinnati Electronics (CE) has developed a Global Positioning Satellite (GPS) Receiver/Transmitter Unit (RTU), specifically for use with launch vehicles. The CE GPS RTU was flown as an experiment on the Missile Technology Demonstration (MTD) flight at White Sands Missile Range (WSMR). This paper provides an overview of CE’s GPS RTU and provides the results of CE’s GPS RTU MTD-3 flight performance.

International Telemetering Conference Proceedings / October 27-30, 1997 / Riviera Hotel and Convention Center, Las Vegas, Nevada / The Vessel Traffic Management System is a cooperative effort of the Naval Undersea Warfare Center and the Naval Air Warfare Center Aircraft Division, funded by the OSD's Test Technology Development and Demonstration Program. The project is establishing the capability to acquire ship tracking information from numerous sources (GPS and radar target extractors), and combine them into a comprehensive, integrated view of the range safety target area. The consolidated tracking information will be transmitted to range safety vessel personnel and presented on portable display systems to aid in clearing the surveillance area of unauthorized vessels. The communications module is media independent in that positional and image data can be routed via RF modem, cellular phone, Intranet or Internet, singly or in any combination. The software systems for data acquisition, display and control are also platform independent, with the system under development operating under WindowsNT and Windows95. Additionally, the use of Java and VRML tools permits a user to display data (including three dimensional presentations of the data) without requiring the applications software. This system has numerous applications including range safety, commercial vessel traffic management, port authority and services monitoring, and oceanographic data gathering.

International Telemetering Conference Proceedings / October 28-31, 1996 / Town and Country Hotel and Convention Center, San Diego, California / This paper contains a description of a new technology tracking feed and a discussion of the features which make this feed unique and allow it to perform better than any other comparable feed. Also included in this report are measured primary antenna patterns, measured and estimated phase tracking performance and estimated aperture efficiency. The latter two items were calculated by integrating the measured primary patterns.

ITC/USA 2015 Conference Proceedings / The Fifty-First Annual International Telemetering Conference and Technical Exhibition / October 26-29, 2015 / Bally's Hotel & Convention Center, Las Vegas, NV / Tracking small marmosets over a large area represents a significant challenge for researchers. The native habitat for such animals are generally unsuitable for GPS based location systems, and the size of the animals prevents large, feature-rich collars from being utilized. Additionally, costs and feasibility prevent researchers from continuously monitoring these animals on the ground. This paper proposes a new system of tracking that offsets complexity from the collar onto fixed Base Stations (BS). The simplified collars emit a ping that multiple BSs then log along with the power of the signal. Combining the data from different BSs allows for the determination of the Signal of Interest (SOI). It was found that using three BSs provided enough accuracy to determine the location of an SOI within an accuracy of 2 m² over a roughly 450 m² area.

published_or_final_version / Electrical Engineering / Master / Master of Philosophy

Self-tracking practices are growing in popularity worldwide. From heart-rate monitoring to mood tracking, many believe that wearable technologies are making their users more mindful in exclusively positive ways. However, I will argue that consistent and deliberate self-tracking (with or without portable devices) necessitates a particular understanding of the self with consequences that have yet to be fully explored. Through an analysis of forum posts on a popular self-tracking discussion and informational site, QuantifiedSelf.com, I will claim that self-trackers approach the creation of self-knowledge in a manner that is particular to today’s society. I will discuss how the ubiquitous conflation of numerical identities with objective reasoning feeds into a mindset that supports quantification of the self, and how the views of self exhibited by these self-trackers can be considered a version of creating a “scientific self.” The notion of the scientific self supports both an individual and societal shift in the practice of “being”—a shift that carries with it many possible repercussions that have yet to be widely analyzed. This analysis, I will argue, is key to limiting the destructive potential of understanding people in terms of data, while simultaneously enabling new conceptualizations of self to be practiced in modern society.

This thesis investigates the improvements that can be made to Bayesian passive sonar tracking in the context of active-passive sonar data fusion. Performance improvements are achieved by exploiting the prior information available within a typical Bayesian data fusion framework. The algorithms developed are tested against both simulated data and data measured during the SEABAR 07 sea trial. Results show that the proposed approaches achieve improved detection, decreased estimation error, and the ability to track quiet targets in the presence of loud interferers. / text

The tabu search particle filter is proposed in this research based on the integration of the modified tabu search metaheuristic optimization and the genetic particle filter. Experiments with this algorithm in real time human tracking applications in unconstrained environments show that it is more robust, accurate and faster than a number of other existing metaheuristic filters, including the evolution particle filter, particle swarm filter, simulated annealing filter, path relink filter and scatter search filter. Quantitative evaluation illustrates that even with only ten particles in the system, the proposed tabu search particle filter has a success rate of 93.85% whereas the success rate of other metaheuristic filters ranged from 68.46% to 17.69% under the same conditions. The accuracy of the proposed algorithm (with ten particles in the tracking system) is 2.69 pixels on average, which is over 3.85 times better than the second best metaheuristic filters in accuracy and 18.13 times better than the average accuracy of all other filters. The proposed algorithm is also the fastest among all metaheuristic filters that have been tested. It achieves approximately 50 frames per second, which is 1.5 times faster than the second fastest algorithm and nineteen times faster than the average speed of all other metaheuristic filters. Furthermore, a unique colour sequence model is developed in this research based on a degenerated form of the hidden Markov model. Quantitative evaluations based on rigid object matching experiments illustrate that the successful matching rate is 5.73 times better than the widely used colour histogram. In terms of speed, the proposed algorithm achieves twice the successful matching rate in about three quarters of the processing time consumed by the colour histogram model. Overall, these results suggest that the two proposed algorithms would be useful in many applications due to their efficiently, accuracy and ability to robustly track people and coloured objects.

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