| HAL-Inria | Publications, software ... of Inria's scientists |
Conference papers
Learning of scanning strategies for electronic support using predictive state representations
Abstract : In Electronic Support, a receiver must monitor a wide frequency spectrum in which threatening emitters operate. A common approach is to use sensors with high sensitivity but a narrow band-width. To maintain surveillance over the whole spectrum, the sensor has to sweep between frequency bands but requires a scanning strategy. Search strategies are usually designed prior to the mission using an approximate knowledge of illumination patterns. This often results in open-loop policies that cannot take advantage of previous observations. As pointed out in past researches, these strategies lack of robustness to the prior. We propose a new closed loop search strategy that learns a stochastic model of each radar using predic-tive state representations. The learning algorithm benefits from the recent advances in spectral learning and rank minimization using nuclear norm penalization.
Cited literature [27 references]
https://hal.inria.fr/hal-01225807
Contributor : Olivier Pietquin <>
Submitted on : Tuesday, November 10, 2015 - 10:40:24 PM
Last modification on : Thursday, April 4, 2019 - 10:18:05 AM
Document(s) archivé(s) le : Friday, February 12, 2016 - 5:08:54 PM
Contributor : Olivier Pietquin <>
Submitted on : Tuesday, November 10, 2015 - 10:40:24 PM
Last modification on : Thursday, April 4, 2019 - 10:18:05 AM
Document(s) archivé(s) le : Friday, February 12, 2016 - 5:08:54 PM
File
MLSP_2015_HGCEJFGOP.pdf
Files produced by the author(s)