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Weighted least squares algorithm for target localization in distributed MIMO radar

Einemo, Martin LU and So, Hing Cheung (2015) In Signal Processing 115. p.144-150
Abstract
In this paper, we address the problem of locating a target using multiple-input multiple-output (MIMO) radar with widely separated antennas. Through linearizing the bistatic range measurements, which correspond to the sum of transmitter-to-target and target-to-receiver distances, a quadratically constrained quadratic program (QCQP) for target localization is formulated. The solution of the QCQP is proved to be an unbiased position estimate whose variance equals the Cramer-Rao lower bound. A weighted least squares algorithm is developed to realize the QCQP. Simulation results are included to demonstrate the high accuracy of the proposed MIMO radar positioning approach.
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author
and
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Multiple-input multiple-output (MIMO) radar, Target localization, Bistatic range, Weighted least squares
in
Signal Processing
volume
115
pages
144 - 150
publisher
Elsevier
external identifiers
  • wos:000356126500013
  • scopus:84928811160
ISSN
0165-1684
DOI
10.1016/j.sigpro.2015.04.004
language
English
LU publication?
yes
id
ff801280-9466-41ca-bc2c-7be68c97565a (old id 7601978)
date added to LUP
2016-04-01 13:27:52
date last changed
2022-04-21 21:47:17
@article{ff801280-9466-41ca-bc2c-7be68c97565a,
  abstract     = {{In this paper, we address the problem of locating a target using multiple-input multiple-output (MIMO) radar with widely separated antennas. Through linearizing the bistatic range measurements, which correspond to the sum of transmitter-to-target and target-to-receiver distances, a quadratically constrained quadratic program (QCQP) for target localization is formulated. The solution of the QCQP is proved to be an unbiased position estimate whose variance equals the Cramer-Rao lower bound. A weighted least squares algorithm is developed to realize the QCQP. Simulation results are included to demonstrate the high accuracy of the proposed MIMO radar positioning approach.}},
  author       = {{Einemo, Martin and So, Hing Cheung}},
  issn         = {{0165-1684}},
  keywords     = {{Multiple-input multiple-output (MIMO) radar; Target localization; Bistatic range; Weighted least squares}},
  language     = {{eng}},
  pages        = {{144--150}},
  publisher    = {{Elsevier}},
  series       = {{Signal Processing}},
  title        = {{Weighted least squares algorithm for target localization in distributed MIMO radar}},
  url          = {{http://dx.doi.org/10.1016/j.sigpro.2015.04.004}},
  doi          = {{10.1016/j.sigpro.2015.04.004}},
  volume       = {{115}},
  year         = {{2015}},
}