Target Detection Architecture for Resource Constrained Wireless Sensor Networks within Internet of Things

Wireless sensor networks (WSN) within Internet of Things (IoT) have the potential
to address the growing detection and classi�cation requirements among many
surveillance applications. RF sensing techniques are the next generation technologies
which o�er 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 re
ected 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 de�ned to quantify the ease of detecting the signal and energy
e�ciency of the signal based on which ease of detection index and energy e�ciency
index respectively have been generated. The waveform selection criterion proposed
in this thesis takes the WSN sensing conditions into account and identi�es the
optimum transmit waveform within the available choices of transmit waveforms
based on their respective ease of detection and energy e�ciency 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 classi�ed 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.