Unscented Transform based Low Complexity Performance Assessment for Adaptive Linearly Constrained Minimum Variance Filters
Ferreira Júnior RS, da Costa JP, Zelenovsky R, de Menezes LR, de Lima DV, Galdo GD (2016)
Publication Type: Conference contribution
Publication year: 2016
Publisher: VDE Verlag GmbH
Pages Range: 39-44
Conference Proceedings Title: 19th International Conference on OFDM and Frequency Domain Techniques, ICOF 2016
Event location: Essen, DEU
ISBN: 9783800742530
Abstract
Linearly Constrained Minimum Variance (LCMV) filters are applied in communication and RADAR systems. In order to evaluate the performance of these filters, Monte Carlo (MC) simulations are commonly employed despite their high computational complexity. This paper proposes a low complexity performance assessment based on the Unscented Transform (UT). With only 32 iterations, the performance evaluation curves of the UT based approach superpose the curves of a thousand MC iterations. Since the computational complexity of one UT iteration is approximately the same as that of a MC iteration, the proposed solution drastically reduces the required time for performance evaluations.
Involved external institutions
Brazil (BR)
Germany (DE)How to cite
APA:
Ferreira Júnior, R.S., da Costa, J.P., Zelenovsky, R., de Menezes, L.R., de Lima, D.V., & Galdo, G.D. (2016). Unscented Transform based Low Complexity Performance Assessment for Adaptive Linearly Constrained Minimum Variance Filters. In 19th International Conference on OFDM and Frequency Domain Techniques, ICOF 2016 (pp. 39-44). Essen, DEU: VDE Verlag GmbH.
MLA:
Ferreira Júnior, Ronaldo S., et al. "Unscented Transform based Low Complexity Performance Assessment for Adaptive Linearly Constrained Minimum Variance Filters." Proceedings of the 19th International Conference on OFDM and Frequency Domain Techniques, ICOF 2016, Essen, DEU VDE Verlag GmbH, 2016. 39-44.
BibTeX: Download