Reference : Physics-Based Cognitive Radar Modeling and Parameter Estimation
Scientific congresses, symposiums and conference proceedings : Paper published in a book
Engineering, computing & technology : Electrical & electronics engineering
http://hdl.handle.net/10993/49512
Physics-Based Cognitive Radar Modeling and Parameter Estimation
English
Sedighi, Saeid mailto [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 []
2022
IEEE Radar Conference
Yes
IEEE Radar Conference
from 21-03-2022 to 25-03-2022
New York City
USA
[en] Cognitive fully adaptive radar (CoFAR) ; con-strained channel estimation ; physics-based mode
[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.
Researchers ; Professionals ; Students
http://hdl.handle.net/10993/49512

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