Title of article :
Adaptation of Rejection Algorithms for a Radar Clutter
Author/Authors :
Popov, D the Department of Radio Engineering Systems - Ryazan State Radio Engineering University (RSREU) - ul. Gagarina, Ryazan' - Ryazanskaya oblast', Russia , Smolskiy, S the Department of Radio Signals Formation and Processing - National Research University (MPEI) - ul. Krasnokazarmennaya, Moscow, Russia
Pages :
6
From page :
228
To page :
233
Abstract :
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.
Keywords :
Adaptation , Clutter , Wobbulation of Repetition Period , Rejection Algorithms
Journal title :
Iranian Journal of Electrical and Electronic Engineering(IJEEE)
Serial Year :
2017
Record number :
2504635
Link To Document :
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