By Topic

Localization and tracking of multiple near-field sources using randomly distributed sensors

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Borah, D.K. ; Klipsch Sch. of Electr. & Comput. Eng., New Mexico State Univ., Las Cruces, NM, USA ; Balagopal, A.

The performance of the maximum likelihood (ML) estimator using fast and adaptive simulated annealing methods has been investigated for near-field localization of multiple narrowband sources. The estimation results are found to be close to the Cramer-Rao lower bound (CRLB). The effect of unknown parameters such as the source frequency, amplitudes and path loss factors is studied. The performance is found to improve with the increase in the signal-to-noise ratio (SNR) and snapshots. It is observed that nonlinearly quantized received samples can be successfully used in the ML estimator with little compromise in localization performance. An increase in the number of sensors, beyond a certain threshold number of sensors located closer to the sources, is found to provide only a marginal improvement in location estimation performance.

Published in:

Signals, Systems and Computers, 2004. Conference Record of the Thirty-Eighth Asilomar Conference on  (Volume:2 )

Date of Conference:

7-10 Nov. 2004