Use this URL to cite or link to this record in EThOS:
Title: Target detection architecture for resource constrained wireless sensor networks within Internet of Things
Author: Bolisetti, Siva Karteek
ISNI:       0000 0004 6424 678X
Awarding Body: Staffordshire University
Current Institution: Staffordshire University
Date of Award: 2017
Availability of Full Text:
Access from EThOS:
Access from Institution:
Wireless sensor networks (WSN) within Internet of Things (IoT) have the potential to address the growing detection and classification requirements among many surveillance applications. RF sensing techniques are the next generation technologies which offer distinct advantages over traditional passive means of sensing such as acoustic and seismic which are used for surveillance and target detection applications of WSN. RF sensing based WSN within IoT detect the presence of designated targets by transmitting RF signals into the sensing environment and observing the reflected echoes. In this thesis, an RF sensing based target detection architecture for surveillance applications of WSN has been proposed to detect the presence of stationary targets within the sensing environment. With multiple sensing nodes operating simultaneously within the sensing region, diversity among the sensing nodes in the choice of transmit waveforms is required. Existing multiple access techniques to accommodate multiple sensing nodes within the sensing environment are not suitable for RF sensing based WSN. In this thesis, a diversity in the choice of the transmit waveforms has been proposed and transmit waveforms which are suitable for RF sensing based WSN have been discussed. A criterion have been defined to quantify the ease of detecting the signal and energy efficiency of the signal based on which ease of detection index and energy efficiency index respectively have been generated. The waveform selection criterion proposed in this thesis takes the WSN sensing conditions into account and identifies the optimum transmit waveform within the available choices of transmit waveforms based on their respective ease of detection and energy efficiency indexes. A target detector analyses the received RF signals to make a decision regarding the existence or absence of targets within the sensing region. Existing target detectors which are discussed in the context of WSN do not take the factors such as interference and nature of the sensing environment into account. Depending on the nature of the sensing environment, in this thesis the sensing environments are classified as homogeneous and heterogeneous sensing environments. Within homogeneous sensing environments the presence of interference from the neighbouring sensing nodes is assumed. A target detector has been proposed for WSN within homogeneous sensing environments which can reliably detect the presence of targets. Within heterogeneous sensing environments the presence of clutter and interfering waveforms is assumed. A target detector has been proposed for WSN within heterogeneous sensing environments to detect targets in the presence of clutter and interfering waveforms. A clutter estimation technique has been proposed to assist the proposed target detector to achieve increased target detection reliability in the presence of clutter. A combination of compressive and two-step target detection architectures has been proposed to reduce the transmission costs. Finally, a 2-stage target detection architecture has been proposed to reduce the computational complexity of the proposed target detection architecture.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available