Volume 13, Issue 3 (September 2017)                   IJEEE 2017, 13(3): 228-233 | Back to browse issues page


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Popov D, Smolskiy S. Adaptation of Rejection Algorithms for a Radar Clutter. IJEEE 2017; 13 (3) :228-233
URL: http://ijeee.iust.ac.ir/article-1-978-en.html
Abstract:   (4273 Views)

In this paper, the algorithms for adaptive rejection of a radar clutter are synthesized for the case of a priori unknown spectral-correlation characteristics at wobbulation of a repetition period of the radar signal. The synthesis of algorithms for the non-recursive adaptive rejection filter (ARF) of a given order is reduced to determination of the vector of weighting coefficients, which realizes the best effectiveness index for radar signal extraction from the moving targets on the background of the received clutter. As the effectiveness criterion, we consider the averaged (over the Doppler signal phase shift) improvement coefficient for a signal-to-clutter ratio (SCR). On the base of extreme properties of the characteristic numbers (eigennumbers) of the matrices, the optimal vector (according to this criterion maximum) is defined as the eigenvector of the clutter correlation matrix corresponding to its minimal eigenvalue. The general type of the vector of optimal ARF weighting coefficients is de-termined and specific adaptive algorithms depending upon the ARF order are obtained, which in the specific cases can be reduced to the known algorithms confirming its authenticity. The comparative analysis of the synthesized and known algorithms is performed. Significant bene-fits are established in clutter rejection effectiveness by the offered processing algorithms compared to the known processing algorithms.

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Type of Study: Research Paper | Subject: Radar and Sonar
Received: 2016/08/05 | Revised: 2017/12/09 | Accepted: 2017/07/20

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© 2022 by the authors. Licensee IUST, Tehran, Iran. This is an open access journal distributed under the terms and conditions of the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) license.