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Quantitative Evaluation of Channel Micro-Doppler Capacity for MIMO UWB Radar Human Activity Signals Based on Time–Frequency Signatures

机译:基于时频签名的MIMO UWB雷达人活动信号通道微多普勒能力的定量评估

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摘要

A novel quantitative method to evaluate channel micro-Doppler capacity of multiple-input and multiple-output (MIMO) system is proposed here. The method is valid for ultrawideband (UWB) MIMO radar human activity systems based on time-frequency signatures, and the quality measure will be noted as a relative signal to noise ratio (RSNR). The method quantifies these signatures and evaluates the relative superiority or inferiority of these MIMO channels. Examples of micro-Doppler signature (mu Ds) characteristics of human activities in a channel will be considered and compared to that of all other channels. First, the MIMO UWB radar human activity signal is modeled, and its corresponding time-frequency (T- F) characteristics are analyzed to justify the rationality of using the new RSNR metric. Second, the method is evaluated using experimental data and the capability of distinguishing the mu D capacity differences among channels is demonstrated. This new method clearly and accurately shows much better visible mu D evaluation performance than that of the conventional signal to noise ratio in time domain (SNRt). Moreover, this evaluation method can still work well, even for signals with low signal to noise ratio (SNR) down to -4-dB level. Therefore, it can be successfully used to select the superior channels and eliminate any inferior channels or provide confidence coefficients for the collected multiple channel data of human activities. This method should lead to a significant reduction of the inferior channels' influence on further MIMO-based classification or imaging of human activities.
机译:提出了一种评价多输入和多输出(MIMO)系统的信道微多普勒容量的新型定量方法。该方法对于基于时频签名的超广域带(UWB)MIMO雷达人类活动系统是有效的,并且将注意到质量测量作为噪声比(RSNR)的相对信号。该方法量化这些签名并评估这些MIMO通道的相对优势或自卑感。将考虑和与所有其他通道的人类活动中的人类活动的微多普勒签名(MU DS)特征的实例。首先,模拟MIMO UWB雷达人类活动信号,并分析其相应的时频(T-F)特性以证明使用新的RSNR度量的合理性。其次,使用实验数据评估该方法,并证明了区分沟道之间的MU D容量差异的能力。这种新方法清楚准确地显示了比时域(SNRT)中的传统信号到噪声比的更好的可见MU D评估性能。此外,这种评估方法仍然可以很好地运行,即使对于低信噪比(SNR)低于-4-DB电平的信号也是如此。因此,可以成功地用于选择上级通道并消除任何劣质通道或提供用于收集的人类活动的多通道数据的置信系数。该方法应导致差距对较差的基于MIMO的分类或人类活动成像的影响显着降低。

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