Optimal Carrier Frequency Design for Frequency Diverse Array Mimo Radar
Cheng, Jie ; Juhlin, Maria LU ; Wang, Wen Qin and Jakobsson, Andreas LU
(2023)
48th IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2023
In ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
2023-June.
- Abstract
In this work, we introduce a novel approach for designing the transmit frequency offset scheme based on Cramér-Rao lower bound (CRLB) minimization for a frequency diverse array multiple-input multiple-output (FDA-MIMO) radar. The problem originates in non-uniform FDA radar where each frequency offset scheme derives from a specific mathematical model, but where no optimization is conducted with respect to the frequency offset design. We propose two frequency selection schemes for FDA-MIMO radar based on A-optimal minimization, both incorporating a priori knowlegdge. The worst case optimal FDA-MIMO (OFDA-MIMOW) radar forms the frequency selection by minimizing the CRLB over a grid of the unknown parameters, whereas the Bayesian optimal... (More)
In this work, we introduce a novel approach for designing the transmit frequency offset scheme based on Cramér-Rao lower bound (CRLB) minimization for a frequency diverse array multiple-input multiple-output (FDA-MIMO) radar. The problem originates in non-uniform FDA radar where each frequency offset scheme derives from a specific mathematical model, but where no optimization is conducted with respect to the frequency offset design. We propose two frequency selection schemes for FDA-MIMO radar based on A-optimal minimization, both incorporating a priori knowlegdge. The worst case optimal FDA-MIMO (OFDA-MIMOW) radar forms the frequency selection by minimizing the CRLB over a grid of the unknown parameters, whereas the Bayesian optimal FDA-MIMO (OFDA-MIMO-B) radar instead minimizes the Bayesian CRLB (BCRLB). The performances of the methods are evaluated using simulated data and compared to other common frequency selection schemes.
(Less)
- author
- Cheng, Jie
; Juhlin, Maria
LU
; Wang, Wen Qin
and Jakobsson, Andreas
LU
- organization
- publishing date
- 2023
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- keywords
- BCRLB, CRLB, FDA-MIMO, frequency offset optimization, MIMO radar
- host publication
- ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing, Proceedings
- series title
- ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
- volume
- 2023-June
- publisher
- IEEE - Institute of Electrical and Electronics Engineers Inc.
- conference name
- 48th IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2023
- conference location
- Rhodes Island, Greece
- conference dates
- 2023-06-04 - 2023-06-10
- external identifiers
-
- scopus:85177608881
- ISSN
- 1520-6149
- ISBN
- 9781728163277
- DOI
- 10.1109/ICASSP49357.2023.10095867
- language
- English
- LU publication?
- yes
- id
- 10429ca1-2625-4fc3-adf5-13888904aa51
- date added to LUP
- 2024-01-08 15:45:07
- date last changed
- 2024-01-09 09:44:27
@inproceedings{10429ca1-2625-4fc3-adf5-13888904aa51,
abstract = {{<p>In this work, we introduce a novel approach for designing the transmit frequency offset scheme based on Cramér-Rao lower bound (CRLB) minimization for a frequency diverse array multiple-input multiple-output (FDA-MIMO) radar. The problem originates in non-uniform FDA radar where each frequency offset scheme derives from a specific mathematical model, but where no optimization is conducted with respect to the frequency offset design. We propose two frequency selection schemes for FDA-MIMO radar based on A-optimal minimization, both incorporating a priori knowlegdge. The worst case optimal FDA-MIMO (OFDA-MIMOW) radar forms the frequency selection by minimizing the CRLB over a grid of the unknown parameters, whereas the Bayesian optimal FDA-MIMO (OFDA-MIMO-B) radar instead minimizes the Bayesian CRLB (BCRLB). The performances of the methods are evaluated using simulated data and compared to other common frequency selection schemes.</p>}},
author = {{Cheng, Jie and Juhlin, Maria and Wang, Wen Qin and Jakobsson, Andreas}},
booktitle = {{ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing, Proceedings}},
isbn = {{9781728163277}},
issn = {{1520-6149}},
keywords = {{BCRLB; CRLB; FDA-MIMO; frequency offset optimization; MIMO radar}},
language = {{eng}},
publisher = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}},
series = {{ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings}},
title = {{Optimal Carrier Frequency Design for Frequency Diverse Array Mimo Radar}},
url = {{http://dx.doi.org/10.1109/ICASSP49357.2023.10095867}},
doi = {{10.1109/ICASSP49357.2023.10095867}},
volume = {{2023-June}},
year = {{2023}},
}