基于CRLBs的多目标雷达位置和速度估计

IF 1.3 Q3 ENGINEERING, ELECTRICAL & ELECTRONIC
N. Rojhani, M. Greco, F. Gini
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引用次数: 2

摘要

在本文中,我们研究了在复杂椭圆对称(CES)分布的相关非高斯杂波中工作的广泛分离多输入多输出(MIMO)雷达目标位置和速度的联合估计问题。更具体地说,我们推导了目标用Swerling 0模型建模,杂波为复t分布时的cram - rao下界(CRLBs)。我们深入分析了杂波相关性和尖峰性的影响,以提供准确的性能估计。索引项- cramims - rao下界(CRLBs), MIMO雷达,位置和速度估计,性能分析,复杂椭圆对称(CES)分布和复杂t分布。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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 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.
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