Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/4057
Title: Multipath exploitation radar with adaptive detection in partially homogeneous environments
Authors: Gülen Yılmaz, Seden Hazal
Taha Hayvacı, Harun
Keywords: Gaussian distribution
Gaussian processes
covariance matrices
object detection
radar detection
vectors
adaptive signal detection
adaptive radar
radar clutter
multipath exploitation radar
adaptive detection
partially homogeneous environments
point-like targets
partially homogeneous Gaussian disturbance
unknown scaling factor
noise contribution
training samples
target echo
direct plus multipath components
multipath returns
scattered signals
glistening surface
multipath echoes
random vector
unknown covariance matrix
constrained generalised likelihood ratio test
primary data covariance structure
noise scaling factor
multipath contribution
constant false alarm rate property
unknown parameters
diffuse multipath conditions
Issue Date: Oct-2020
Publisher: Institution of Engineering and Technology
Source: Yilmaz, S. H. G., and Hayvaci, H. T. (2020). Multipath exploitation radar with adaptive detection in partially homogeneous environments. IET Radar, Sonar and Navigation, 14(10), 1475-1482.
Abstract: The authors deal with the problem of detecting point-like targets in the presence of diffuse multipath under the assumption of a partially homogeneous Gaussian disturbance by introducing an unknown scaling factor which represents the mismatch between the noise contribution of the cell under test and the training samples. Also, they model the target echo as a superposition of direct plus multipath components where multipath returns are thought of as scattered signals from a glistening surface. Hence, multipath echoes are represented as a Gaussian distributed random vector with an unknown covariance matrix. Then, the authors derive a constrained generalised likelihood ratio test under the assumption that the primary data covariance structure is similar to the covariance matrix obtained from training samples where the degree of similarity is up to both noise scaling factor and multipath contribution. Besides, they prove that the proposed detector ensures constant false alarm rate (CFAR) property with respect to the unknown parameters. Finally, they compared the devised algorithm with the commonly used CFAR estimators. The results show that the proposed detector copes well with diffuse multipath conditions under partially homogeneous environments.
URI: https://hdl.handle.net/20.500.11851/4057
https://digital-library.theiet.org/content/journals/10.1049/iet-rsn.2020.0059
ISSN: 1751-8784
Appears in Collections:Elektrik ve Elektronik Mühendisliği Bölümü / Department of Electrical & Electronics Engineering
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection

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