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Ziv–Zakai Bound for Joint Parameter Estimation in MIMO Radar Systems

机译:Ziv–Zakai界用于MIMO雷达系统中的联合参数估计

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Local bounds, such as the Cramer–Rao bound (CRB), provide inaccurate predictions under low signal-to-noise ratio (SNR) conditions. Global bounds are capable of providing more accurate predictions of the performance of estimators over the full range of SNR. In this paper, we derive the Ziv–Zakai bound (ZZB) for joint location and velocity estimation of a target illuminated by a non-coherent multiple-input multiple-output (MIMO) radar employing orthogonal waveforms and widely spaced antennas. The setup captures the multistatic nature of the target gains, where each pair of transmit-receive elements experience independent gains governed by the Swerling type 1 model. The target returns are observed in the presence of spatially and temporally independent Gaussian clutter-plus-noise. The ZZB for joint delay and Doppler estimation for single-input and single-output (SISO) radar is also developed. We show that the ZZB is a comprehensive metric that captures the effect of the SNR, the ambiguity function (AF) and other parameters of the radar systems. The effects of different system configurations are explored through numerical studies. The results are useful for the analysis of both active and passive radars.
机译:局部边界,例如Cramer-Rao边界(CRB),在低信噪比(SNR)条件下提供的预测不准确。全局范围能够在整个SNR范围内提供更准确的估算器性能预测。在本文中,我们推导了Ziv–Zakai边界(ZZB),用于联合定位和速度估算目标,该目标由采用正交波形和宽间隔天线的非相干多输入多输出(MIMO)雷达照亮。该设置捕获了目标增益的多静态特性,其中每对发射-接收元件都经历由Swerling 1型模型控制的独立增益。在存在空间和时间独立的高斯杂波加噪声的情况下,可以观察到目标收益。还开发了用于单输入单输出(SISO)雷达的联合延迟和多普勒估计的ZZB。我们表明,ZZB是一个综合指标,可捕获SNR,模糊函数(AF)和雷达系统其他参数的影响。通过数值研究探索了不同系统配置的影响。该结果对于有源和无源雷达的分析都是有用的。

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