TY - JOUR
T1 - An Overview of Parametric Modeling and Methods for Radar Target Detection with Limited Data
AU - Wang, Fangzhou
AU - Wang, Pu
AU - Zhang, Xin
AU - Li, Hongbin
AU - Himed, Braham
N1 - Publisher Copyright:
© 2013 IEEE.
PY - 2021
Y1 - 2021
N2 - This article provides a survey of recent results on exploiting parametric auto-regressive (AR) models for adaptive radar target detection. Specifically, three types of radar systems are considered, including phased-array radar with multiple co-located transmitters and receivers, distributed multi-input multi-output (MIMO) radar with widely and spatially separated transmitters and receivers, and passive radar which uses existing sources as illuminators of opportunity (IOs). These radar systems are of significant interest for a wide range of military and civilian applications. For each of the three types of radars, we discuss how AR processes can be employed to succinctly model the underlying signal correlation and efficiently estimate it from limited data, thus enabling effective target detection in complex non-homogeneous environments when training data is limited. We illustrate the performance of such parametric model assisted detectors relative to conventional non-parametric approaches by using computer simulated and experimental data.
AB - This article provides a survey of recent results on exploiting parametric auto-regressive (AR) models for adaptive radar target detection. Specifically, three types of radar systems are considered, including phased-array radar with multiple co-located transmitters and receivers, distributed multi-input multi-output (MIMO) radar with widely and spatially separated transmitters and receivers, and passive radar which uses existing sources as illuminators of opportunity (IOs). These radar systems are of significant interest for a wide range of military and civilian applications. For each of the three types of radars, we discuss how AR processes can be employed to succinctly model the underlying signal correlation and efficiently estimate it from limited data, thus enabling effective target detection in complex non-homogeneous environments when training data is limited. We illustrate the performance of such parametric model assisted detectors relative to conventional non-parametric approaches by using computer simulated and experimental data.
KW - Parametric modeling
KW - adaptive target detection
KW - distributed multi-input multi-output (MIMO) radar
KW - passive radar
KW - phased-array radar
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U2 - 10.1109/ACCESS.2021.3074063
DO - 10.1109/ACCESS.2021.3074063
M3 - Review article
AN - SCOPUS:85107195403
VL - 9
SP - 60459
EP - 60469
JO - IEEE Access
JF - IEEE Access
M1 - 9406810
ER -