基于cram - rao边界的MIMO雷达波形高精度幅值估计设计

Ping Huang;Bo Tang;Wenjun Wu;Xinkuang Wang
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引用次数: 0

摘要

本文主要研究多输入多输出(MIMO)雷达系统的发射波形设计。设计目标是提高MIMO雷达在彩色噪声环境下的目标幅度估计性能。为此,我们利用目标幅度估计误差上的cram r - rao界(CRB)作为设计度量。此外,对传输波形施加峰均功率比(PAPR)约束,以减轻功率放大器引起的非线性失真。为了解决公式化的非凸问题,我们提出了两种迭代算法:一种利用乘法器的交替方向方法(ADMM),另一种使用最小化最大化(MM)。实验结果表明,所设计的波形比同类波形具有更低的CRB和更小的幅度估计误差。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Cramér–Rao Bound-Based MIMO Radar Waveform Design for High-Precision Amplitude Estimation
This article focuses on the transmit waveform design for multiple-input multiple-output (MIMO) radar systems. The design goal is to enhance the target amplitude estimation performance of MIMO radar in colored noise. To this purpose, we utilize the Cramér–Rao bound (CRB) on the target amplitude estimation error as the design metric. Additionally, a peak-to-average power ratio (PAPR) constraint is imposed on the transmitted waveforms to mitigate the nonlinear distortions caused by the power amplifier. To address the formulated nonconvex problem, we propose two iterative algorithms: one leveraging the alternating direction method of multipliers (ADMM) and the other using minorization–maximization (MM). The experimental results demonstrate that the designed waveforms achieve lower CRB and reduced amplitude estimation errors than the counterparts.
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