By Topic

Asymptotic properties of nonlinear weighted least squares in radar array processing

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Eriksson, J. ; Airborne Radar Div., Ericsson Microwave Syst. AB, Molndal, Sweden ; Viberg, M.

This paper treats nonlinear weighted least squares parameter estimation of sinusoidal signals impinging on a sensor array. We give a consistency proof for a more general model than what has been previously considered in the analysis of two-dimensional (2-D) sinusoidal fields. Specifically, the array can have an arbitrary shape, and spatially colored noise is allowed. Further, we do not impose the restriction of unique frequencies within each dimension, and the number of samples is assumed large in only the temporal dimension. In addition to consistency, we establish that the parameter estimates are multivariate Gaussian distributed under a large class of noise distributions. The finite sample performance is investigated via computer simulations, which illustrate that a recommended two-step procedure yields asymptotically efficient estimates when the noise is Gaussian. The first step is necessary for estimating the weighting matrix, which has a dramatic influence on the performance in the studied scenarios. The number of samples required to attain the Crame´r-Rao lower bound is found to coincide with the point where the signal sources are separated by more than one discrete Fourier transform bin. This remains true even when the signals emanate from the same direction of arrival (DOA).

Published in:

Signal Processing, IEEE Transactions on  (Volume:52 ,  Issue: 11 )