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Designing Optimal Frequency Offsets for Frequency Diverse Array MIMO Radar

Cheng, Jie LU ; Juhlin, Maria LU ; Jakobsson, Andreas LU orcid and Wang, Wen Qin (2023) In IEEE Transactions on Aerospace and Electronic Systems 59(6). p.8104-8118
Abstract

Frequency diverse array (FDA) radars provide a potential solution to target localisation along the slant range and azimuth angle due to the range-angle-dependent transmit beampattern caused by the used frequency increments. However, the S -shaped beampattern resulting from the standard FDA leads to multiple candidate location estimates, introducing ambiguity in the target localization. To make full use of the degrees of freedom (DOF) allowed by the frequency increments, we here propose an optimal FDA multiple-input multiple-output (MIMO) frequency design scheme based on the Cramér-Rao lower bound (CRLB). The resulting system, here termed the optimal FDA-MIMO (OFDA-MIMO), is formed by optimizing the expected localization... (More)

Frequency diverse array (FDA) radars provide a potential solution to target localisation along the slant range and azimuth angle due to the range-angle-dependent transmit beampattern caused by the used frequency increments. However, the S -shaped beampattern resulting from the standard FDA leads to multiple candidate location estimates, introducing ambiguity in the target localization. To make full use of the degrees of freedom (DOF) allowed by the frequency increments, we here propose an optimal FDA multiple-input multiple-output (MIMO) frequency design scheme based on the Cramér-Rao lower bound (CRLB). The resulting system, here termed the optimal FDA-MIMO (OFDA-MIMO), is formed by optimizing the expected localization estimation accuracy, given the available prior knowledge of potential target locations. We examine two different modeling scenarios, one where the prior information is known up to intervals on the parameters, formulated using the worst case CRLB (WCRLB), and one where the parameters are known to come from prior distributions, formulated using the corresponding Bayesian CRLB (BCRLB). The used frequency offsets are found as those minimizing the CRLBs, and may be iteratively refined as further information becomes available in a multi-pulse scenario. Both theoretical analysis and simulation results validate the preferable performance of the proposed system as compared to alternative frequency selection schemes.

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author
; ; and
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Exploiting prior knowledge, frequency diverse array multiple-input multiple-output (FDA-MIMO), Frequency diversity, frequency offset optimization, Location awareness, Manganese, MIMO radar, Radar, Radar antennas, Receiving antennas, Transmitters
in
IEEE Transactions on Aerospace and Electronic Systems
volume
59
issue
6
pages
15 pages
publisher
IEEE - Institute of Electrical and Electronics Engineers Inc.
external identifiers
  • scopus:85166780107
ISSN
0018-9251
DOI
10.1109/TAES.2023.3300819
language
English
LU publication?
yes
id
f5f95555-c1bf-4eeb-b898-3be360bedc9c
date added to LUP
2023-11-21 12:54:57
date last changed
2024-01-09 15:45:01
@article{f5f95555-c1bf-4eeb-b898-3be360bedc9c,
  abstract     = {{<p>Frequency diverse array (FDA) radars provide a potential solution to target localisation along the slant range and azimuth angle due to the range-angle-dependent transmit beampattern caused by the used frequency increments. However, the S -shaped beampattern resulting from the standard FDA leads to multiple candidate location estimates, introducing ambiguity in the target localization. To make full use of the degrees of freedom (DOF) allowed by the frequency increments, we here propose an optimal FDA multiple-input multiple-output (MIMO) frequency design scheme based on the Cram&amp;#x00E9;r-Rao lower bound (CRLB). The resulting system, here termed the optimal FDA-MIMO (OFDA-MIMO), is formed by optimizing the expected localization estimation accuracy, given the available prior knowledge of potential target locations. We examine two different modeling scenarios, one where the prior information is known up to intervals on the parameters, formulated using the worst case CRLB (WCRLB), and one where the parameters are known to come from prior distributions, formulated using the corresponding Bayesian CRLB (BCRLB). The used frequency offsets are found as those minimizing the CRLBs, and may be iteratively refined as further information becomes available in a multi-pulse scenario. Both theoretical analysis and simulation results validate the preferable performance of the proposed system as compared to alternative frequency selection schemes.</p>}},
  author       = {{Cheng, Jie and Juhlin, Maria and Jakobsson, Andreas and Wang, Wen Qin}},
  issn         = {{0018-9251}},
  keywords     = {{Exploiting prior knowledge; frequency diverse array multiple-input multiple-output (FDA-MIMO); Frequency diversity; frequency offset optimization; Location awareness; Manganese; MIMO radar; Radar; Radar antennas; Receiving antennas; Transmitters}},
  language     = {{eng}},
  number       = {{6}},
  pages        = {{8104--8118}},
  publisher    = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}},
  series       = {{IEEE Transactions on Aerospace and Electronic Systems}},
  title        = {{Designing Optimal Frequency Offsets for Frequency Diverse Array MIMO Radar}},
  url          = {{http://dx.doi.org/10.1109/TAES.2023.3300819}},
  doi          = {{10.1109/TAES.2023.3300819}},
  volume       = {{59}},
  year         = {{2023}},
}