Chaotic Staggered PRF and Reduced Rank STAP for Airborne Radar

Samira Dib; Mourad Barkat; Jean-Marie Nicolas; Malek Benslama

doi:10.15866/irease.v7i1.1339

Chaotic Staggered PRF and Reduced Rank STAP for Airborne Radar

Samira Dib^(1*), Mourad Barkat⁽²⁾, Jean-Marie Nicolas⁽³⁾, Malek Benslama⁽⁴⁾

^(*) Corresponding author

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Abstract

This paper is a contribution for the suppression of interferences in monostatic airborne radar detection. We propose to consider the projection approximation subspace tracking (PAST) and orthonormal PAST (OPAST) algorithms for the reduction of the rank. Simulation results are presented and the performance of space-time adaptive processing (STAP) is discussed with a comparative study to the principal components (PC) method. Performance curves show that PAST and OPAST do indeed allow good detection of slow moving targets even with low rank covariance matrix.
In order to achieve good detection performance in the case of Doppler ambiguous environment, we propose a novel idea using the rich properties of chaos. It resides in changing the PRF in a chaotic manner. Results show that this solves well the problem of ambiguities while using a reduced rank STAP. Furthermore, we also show using a chaotic staggered PRF, the recursive algorithms give better results than the methods based on eigenvalues decomposition

Keywords

Airborne Radar; Doppler Frequency; PRF; Recursive Subspace Algorithms; STAP

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