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

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 (<inline-formula> <tex-math notation="LaTeX">$\mu $ </tex-math></inline-formula>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 (<inline-formula> <tex-math notation="LaTeX">$T$ </tex-math></inline-formula>–<inline-formula> <tex-math notation="LaTeX">$F$ </tex-math></inline-formula>) 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 <inline-formula> <tex-math notation="LaTeX">$\mu \text{D}$ </tex-math></inline-formula> capacity differences among channels is demonstrated. This new method clearly and accurately shows much better visible <inline-formula> <tex-math notation="LaTeX">$\mu \text{D}$ </tex-math></inline-formula> evaluation performance than that of the conventional signal to noise ratio in time domain (<inline-formula> <tex-math notation="LaTeX">${\mathrm {SNR}}_{t}$ </tex-math></inline-formula>). 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.