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You searched for +publisher:"Clemson University" +contributor:("Dr. Carl W. Baum, Committee Chair"). Showing records 1 – 2 of 2 total matches.

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Clemson University

1. Bhattacharyya, Upasana. Estimating the location of a Nuclear Source with Multiple Drones in an Urban Environment.

Degree: PhD, Electrical and Computer Engineering (Holcomb Dept. of), 2018, Clemson University

The problem of locating the source of radioactive emissions using a network of sensors is considered. Estimating the three-dimensional location of a nuclear source is especially difficult in environments in which no sensor can be placed in close proximity to the source. In this dissertation, maximum-likelihood (ML) estimation is applied to a Poisson process model for radiation received at sensors that is proportional to the inverse square of the distance between the source and the sensor. The joint multivariate density for the sensors is then maximized in order to estimate the location and strength of the radioactive source. Additionally, a limited number of sensors is used to implement a two-stage adaptive algorithm. In the first stage the drones sit at the center of a building's faces and an approximate location of the radiation source is obtained. Based on the results of the first stage, in the second stage the drones move to additional locations to collect more data. The data from both stages is utilized to obtain a more accurate estimate of the location of the radiation source. A third topic involves the effects of spatially non-homogeneous attenuation due to highly absorbing materials such as concrete. A novel metric is presented for identifying situations in which non-homogeneity significantly skews estimation results. This metric is used to drive a multiple iteration multi-stage estimation algorithm utilizing multiple applications of ML estimation. The algorithm is analyzed in realistic situations such as highly absorbing walls and a central shaft. Finally, a hybrid algorithm is proposed that first determines with a high degree of reliability whether non-homogeneous attenuation is present. If non-homogeneous attenuation is declared absent, the sensors move according to the adaptive algorithm. If non-homogeneous attenuation is declared present, the multiple-iteration algorithm is employed. This hybrid algorithm performs extremely well whether non-homogeneous is present or absent. Advisors/Committee Members: Dr. Carl W. Baum, Committee Chair, Dr. Harlan B. Russell, Dr. Kuang-Ching Wang, Dr. Brook T. Russell.

Subjects/Keywords: Estimation; Maximum Likelihood; Radiation detection; Signal Processing

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Bhattacharyya, U. (2018). Estimating the location of a Nuclear Source with Multiple Drones in an Urban Environment. (Doctoral Dissertation). Clemson University. Retrieved from https://tigerprints.clemson.edu/all_dissertations/2229

Chicago Manual of Style (16th Edition):

Bhattacharyya, Upasana. “Estimating the location of a Nuclear Source with Multiple Drones in an Urban Environment.” 2018. Doctoral Dissertation, Clemson University. Accessed November 14, 2019. https://tigerprints.clemson.edu/all_dissertations/2229.

MLA Handbook (7th Edition):

Bhattacharyya, Upasana. “Estimating the location of a Nuclear Source with Multiple Drones in an Urban Environment.” 2018. Web. 14 Nov 2019.

Vancouver:

Bhattacharyya U. Estimating the location of a Nuclear Source with Multiple Drones in an Urban Environment. [Internet] [Doctoral dissertation]. Clemson University; 2018. [cited 2019 Nov 14]. Available from: https://tigerprints.clemson.edu/all_dissertations/2229.

Council of Science Editors:

Bhattacharyya U. Estimating the location of a Nuclear Source with Multiple Drones in an Urban Environment. [Doctoral Dissertation]. Clemson University; 2018. Available from: https://tigerprints.clemson.edu/all_dissertations/2229


Clemson University

2. Wang, Luyang. Mobile Search Strategies and Detection Analysis of Nuclear Radiation Sources.

Degree: PhD, Electrical Engineering, 2017, Clemson University

This work focuses on detection analysis and search strategies for nuclear radiation sources in metropolitan areas with mobile sensor networks. A mobile sensor detecting a stationary nuclear source experiences continually changing statistics. In this work we provide an analysis of the probability of detection of a nuclear source that incorporates these continual changes. We apply the analysis technique to several patterns of motion including linear and circular paths. Analysis is also presented for cases in which there is a significant vertical offset between source and mobile sensor (the three-dimensional problem). The resulting expressions are computationally simple to evaluate and have application to both analysis and simulation of nuclear detection systems in a variety of scenarios. In metropolitan areas, with vehicles equipped with detectors and Global Position System (GPS) devices, we consider the design of a robust detection system to provide consistent surveillance. Various strategies for providing this surveillance with a mobile sensor network are considered and the results are compared. Both time-from-last-visit based algorithms and detection algorithms that utilize both time and probability-of-miss estimates are considered. The algorithms are shown to perform well in a variety of scenarios, and it is further shown that the algorithms that utilize probability information outperform those that do not. Advisors/Committee Members: Dr. Carl W. Baum, Committee Chair, Dr. Harlan B. Russell, Dr. Robert J. Schalkoff, Dr. Yue Wang.

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Wang, L. (2017). Mobile Search Strategies and Detection Analysis of Nuclear Radiation Sources. (Doctoral Dissertation). Clemson University. Retrieved from https://tigerprints.clemson.edu/all_dissertations/1951

Chicago Manual of Style (16th Edition):

Wang, Luyang. “Mobile Search Strategies and Detection Analysis of Nuclear Radiation Sources.” 2017. Doctoral Dissertation, Clemson University. Accessed November 14, 2019. https://tigerprints.clemson.edu/all_dissertations/1951.

MLA Handbook (7th Edition):

Wang, Luyang. “Mobile Search Strategies and Detection Analysis of Nuclear Radiation Sources.” 2017. Web. 14 Nov 2019.

Vancouver:

Wang L. Mobile Search Strategies and Detection Analysis of Nuclear Radiation Sources. [Internet] [Doctoral dissertation]. Clemson University; 2017. [cited 2019 Nov 14]. Available from: https://tigerprints.clemson.edu/all_dissertations/1951.

Council of Science Editors:

Wang L. Mobile Search Strategies and Detection Analysis of Nuclear Radiation Sources. [Doctoral Dissertation]. Clemson University; 2017. Available from: https://tigerprints.clemson.edu/all_dissertations/1951

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