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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
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
2015-07-24 13:32:20
date last changed
2017-11-19 03:46:24
@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},
  keyword      = {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},
  volume       = {115},
  year         = {2015},
}