CRLBs for Location and Velocity Estimation for MIMO Radars in CES-Distributed Clutter

In this article, we investigate the problem of jointly estimating target location and velocity for widely separated multiple-input multiple-output (MIMO) radar operating in correlated non-Gaussian clutter, modeled by a complex elliptically symmetric (CES) distribution. More specifically, we derive t...

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Bibliographic Details
Main Authors: Neda Rojhani, Maria Sabrina Greco, Fulvio Gini
Format: Article
Language:English
Published: Frontiers Media S.A. 2022-03-01
Series:Frontiers in Signal Processing
Subjects:
Online Access:https://www.frontiersin.org/articles/10.3389/frsip.2022.822285/full
Description
Summary:In this article, we investigate the problem of jointly estimating target location and velocity for widely separated multiple-input multiple-output (MIMO) radar operating in correlated non-Gaussian clutter, modeled by a complex elliptically symmetric (CES) distribution. More specifically, we derive the Cramér–Rao lower bounds (CRLBs) when the target is modeled by the Swerling 0 model and the clutter is complex t-distributed. We thoroughly analyze the impact of the clutter correlation and spikiness to provide accurate performance estimation. Index terms—Cramér–Rao lower bounds (CRLBs), MIMO radar, location and velocity estimation, performance analysis, complex elliptically symmetric (CES) distributed, and complex t-distribution.
ISSN:2673-8198