Fuzzy-based MTD. A fuzzy decisive approach for moving target detection in multichannel SAR framework

Publication Date07 Jan 2020
AuthorEppili Jaya,B.T. Krishna
SubjectLibrary & information science,Librarianship/library management,Library technology,Information behaviour & retrieval,Metadata,Information & knowledge management,Information & communications technology,Internet
Fuzzy-based MTD
A fuzzy decisive approach for
moving target detection in multichannel
SAR framework
Eppili Jaya
Department of ECE, JNTUK University, Kakinada, India and
Department of ECE,
Aditya Institute of Technology and Management, Tekkali, India, and
B.T. Krishna
Department of ECE, JNTUK University, Kakinada, India
Purpose Synthetic aperture radar exploits the receiving signals in the antenna for detecting the moving
targets and estimates the motion parameters of the moving objects. The limitation of the existing methods is
regarding the poor power density such that those received signals are essentially to be transformed to the
background ratio. To overcome this issue, fractional Fourier transform (FrFT) is employed in the moving
target detection (MTD) process. The paper aims to discuss this issue.
Design/methodology/approach The proposed MTD method uses the fuzzy decisive approach for
detecting the moving target in the search space. The received signal and the FrFT of the received signal are
subjected to the calculation of correlation using the ambiguity function. Based on the correlation, the location
of the target is identified in the search space and is fed to the fuzzy decisive module, which detects the target
location using the fuzzy linguistic rules.
Findings The simulation is performed, and the analysis is carried out based on the metrics,
like detection time, missed target rate, and MSE. From the analysis, it can be shown that the proposed
Fuzzy-based MTD process detected the object in 5.0237 secs with a minimum missed target rate of 0.1210 and
MSE of 23377.48.
Originality/value The proposed Fuzzy-MTD is the application of the fuzzy rules for locating the moving
target in search space based on the peak energy of the original received signal and FrFT of the original
received signal.
Keywords Ambiguity function, Fuzzy decisive approach, Matching filter, MTD, Multichannel SAR,
Synthetic aperture radar
Paper type Research paper
1. Introduction
Synthetic aperture radar (SAR) attracts the researchers as they find valuable application
in the military fields and possess the ultimate ability to detect the weather conditions
through the remote sensing principles (Huang et al., 2016). The role of multifunctional
radar concentrates on multiple tasks, including object detection, tracking and high
resolution imaging (Zhang et al., 2011; Yu et al., 2017). Practically, the required energy is
less and is merged with the noise and extending the time of the synthetic aperture brings
the performance of the coherent integration to remain effective such that the SAR image
of high resolution is obtained. It is to be noted that the target cross-track velocity leads to
the migration in the linear range. On the other hand, other target motion parameters,
including the along-track velocity, along-track acceleration and cross-track acceleration,
yield the range curvature and Doppler frequency migration (DFM) when the synthetic
Data Technologies and
Vol. 54 No. 1, 2020
pp. 66-84
© Emerald PublishingLimited
DOI 10.1108/DTA-03-2019-0049
Received 28 March 2019
Revised 19 August 2019
Accepted 29 August 2019
The current issue and full text archive of this journal is available on Emerald Insight at:
This paper forms part of a special section: Knowledge and data mining for recent and advanced
applications using emerging technologies.
aperture time is large. In the case of the situation mentioned above, the quality of the
SAR image becomes poor as a result of the loss of concentration in the target energy
(Yang et al., 2017; Yu et al., 2018). Moreover, SAR processing yields the images with a
better azimuth resolution as they utilize the platform movement for generating a long and
synthetic antenna. The acquisition time remainshighforassuringthebetterresolution.In
addition to the SAR techniques, there are other techniques that act on the moving targets,
separately from non-moving ones (Taylor et al., 2017).
The process of detecting the moving targets from any dynamic and uncertain environments
grabs huge attention as they are employed in the surveillance, intelligence and reconnaissance
systems. The illustration of the reconnaissance systems includes the Secure Border Initiative by
the Department of Homeland Security. A better solution for the moving object detection can be
assured by large distributed networks with passive sensors that are because these sensors offer
better and wider coverage of areas with a considerably less running cost. The sensors are
inbuilt with a higher degree of communication and computing abilities in order to assure a
collective intelligent behavior. The main need for the cost-effective function of these distributed
sensor networks relies on the fact of assuring reliable sensing performance, whereas controlling
the number of communications needed to cause the reliable decision fusion, and above all to be
aware of the situation in the network (Wang et al., 2009; Dongbing, 2011). Additionally, there is a
need for the individual sensors with less computational capabilities, for which they require the
data processing algorithms in order to extract the information from the time series of the signals
that are sensed by the sensors. The hectic problem in a dynamic environment is to finalize the
decision using passive sensing because these sensors are highly sensitive to the uncertainties in
the environment (Li et al., 2017). Several optimization algorithms, such as Bat Algorithm
(Karlekar and Gomathi, 2017) and Lion Algorithm (Ranjan and Prasad, 2018), have been utilized
for object detection.
The range walk is handled using a large number of the linear trajectory searching
methods, suchas Hough transform (Evans, 1994), Radon transform (Zand and Gholami, 2017)
and Radon Fouriertransform (Xu et al., 2011). Moreover,keystone transform (KT) is designed
such that they aim at rescaling the slow time axis and rectify the range walk with no
knowledgeof the kinetic information of the target(Zhu et al., 2007; Yu et al., 2018).On the other
hand, when there isa Doppler ambiguity, KT goes in searchof the ambiguity number. Thus,
the conventional methods are grouped as search-based methods that are subjected to huge
computation complexity as they engage themselves in searching for all possible parameters.
These bottleneckslimit the practical applicationof the search-based methods, wherethere is a
demand for high real-time accuracy and high estimation accuracy (Zhang et al., 2017). Thus,
there is a need for an effective algorithm to eradicate the range migration and DFM, and
it is the area of interest in recent years (Yu et al., 2017). Accordingly, the fractional Fourier
transform (FrFT) dragsinterest from the radar community that can be employed for moving
target detection (MTD) (Sun et al., 2002), beamforming (Yetik and Nehorai, 2003), imaging
(Pelich et al., 2016) and waveform generat ion (Clemente et al., 2014). While concentrating on
MTD, the echo of the moving target is considered as a chirp signal, and the energy of the
signal is computed using FrFT in the Doppler centroid (DC)Doppler frequency rate (DFR)
domain. The computation of the energy of the signal tends to locate the target in the
stationary contribution (Li et al., 2016).
1.1 Challenges in the existing MTD approaches
The movementand the total targets in the search space arenot known in case of the real SAR
data processing that pictures the failure of the ground moving target indication (GMTI)
algorithms. These algorithms suffer from multiple moving objects with multiple motion
features (Yang et al., 2015). The conventional method airborne linear strip map SAR faces
problem due to the prolonged revisit time such that there is an application of the method in

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