Robust subspace-based algorithms for joint angle/Doppler estimation in non-Gaussian clutter

Abstract

We consider the problem of joint angle and Doppler estimation for space-time adaptive processing (STAP) airborne radar in non-Gaussian clutter which is modeled as a complex symmetric alpha stable S α S process. We investigate the performance of the subspace algorithms based on the sign covariance matrix estimate (SCM) which has almost robust performance in heavy tailed noise [S. Visuri, H. Oja, V. Koivunen, Subspace-based direction-of-arrival estimation using non-parametric statistics, IEEE Trans. Signal Process. 49 (September 2001) 2060–2073]. We propose a new class of covariance estimation based on phased fractional lower-order moment (PFLOM). Performance of the proposed technique is assessed through simulations and it is shown that this algorithm reveals better performance than fractional lower order moment (FLOM) and SCM based algorithms [T. Liu, J.M. Mendel, A subspace-based direction finding algorithm using fractional lower order statistics, IEEE Trans. Signal Process. 49 (8) (August 2001) 1605–1613; P. Tsakalides, et al., Angle/Doppler estimation in heavy tailed clutter backgrounds, IEEE Trans. Aerospace Electron. Syst. 35 (2) (April 1999) 419–436; S. Visuri, H. Oja, V. Koivunen, Subspace-based direction-of-arrival estimation using non-parametric statistics, IEEE Trans. Signal Process. 49 (September 2001) 2060–2073].