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Physics-Based Cognitive Radar Modeling and Parameter Estimation
Sedighi, Saeid; Mysore Rama Rao, Bhavani Shankar; Mishra, Kumar Vijay et al.
2022In IEEE Radar Conference
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Keywords :
Cognitive fully adaptive radar (CoFAR); con-strained channel estimation; physics-based mode
Abstract :
[en] We consider the problem of channel response estimation in cognitive fully adaptive radar (CoFAR). We show that this problem can be expressed as a constrained channel estimation problem exploiting the similarity between the channel impulse responses (CIRs) of the adjacent channels. We develop a constrained CIR estimation (CCIRE) algorithm enhancing estimation performance compared to the unconstrained CIR estimation where the similarity between the CIRs of the adjacent channels is not employed. Further, we we derive the Cram\'{e}r-Rao bound (CRB) for the CCIRE and show the optimality of the proposed CCIRE through comparing its performance with the derived CRB.
Disciplines :
Electrical & electronics engineering
Author, co-author :
Sedighi, Saeid ;  University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > SPARC
Mysore Rama Rao, Bhavani Shankar  ;  University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > SPARC
Mishra, Kumar Vijay
Rangaswamy, Muralidhar
External co-authors :
yes
Language :
English
Title :
Physics-Based Cognitive Radar Modeling and Parameter Estimation
Publication date :
2022
Event name :
IEEE Radar Conference
Event place :
New York City, United States
Event date :
from 21-03-2022 to 25-03-2022
Main work title :
IEEE Radar Conference
Peer reviewed :
Peer reviewed
Available on ORBilu :
since 12 January 2022

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