# An Efficient Dynamic Engineering Implementation Architecture for MIMO Radar System
## 5 Results  
### Resource Consumption and Processing Time  
As discussed previously, the proposed system demonstrates significant advantages in terms of reduced storage resource consumption and enhanced real-time performance. To quantitatively assess the performance of this system, we measure the storage resource usage and the time elapsed to process a single data frame. Given that the data volume in the MIMO radar system is influenced by various factors, such as the number of sampling points and antennas, we manipulate the number of transmitting channels to vary the data volume of the system for a comprehensive performance evaluation. Adhering to the principle of univariate experimentation, we fix the number of distance sampling points and speed sampling points at 1024 and 256, respectively. Subsequently, we progressively increase the number of active transmitting antenna channels from 1 to 12, incrementally increasing the number of synthesized virtual antenna channels. We then record and compare the storage resource consumption and system time consumption for configurations with varying numbers of virtual antenna channels.  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Parameter** & **Description** & **Value** \\ \hline \(f_{s}\) & ADC Sample Rate & 8 MHz \\ \(W_{d}\) & Data Bit Width & 32 bits \\ M & ADC Sample Rate & 1024 \\ K & Number of Chirps & 256 \\ \hline \hline \end{tabular}
\end{table}
Table 2: Radar sampling parameters.  
Figure 9: Experimental test scenarios. (**a**) Radar set up real scenarios. (**b**) Radar position relative to the target.  
In the experimental outcomes, depicted in Figure 10, the horizontal axis represents the number of activated transmitting antennas, while the vertical axis indicates the size of the storage resources required by the system. The blue line illustrates the storage resource consumption of a MIMO radar system employing a double storage architecture (DS-MRS), whereas the orange line represents the storage resource consumption for a system utilizing an efficient dynamic storage architecture (ED-MRS). It is evident from the graph that as the number of activated transmitting antenna channels increases, the storage resource requirements for both signal processing systems increase accordingly.  
Notably, at equivalent numbers of transmitting antenna channels, the proposed system utilizes approximately 50% less storage resources than the conventional system. Furthermore, as the number of transmitting antenna channels increases, the growth rate of storage resource consumption in the efficient dynamic MIMO radar system is more gradual. This finding holds substantial relevance for implementing large-scale array MIMO radar projects.  
As depicted in Figure 11, the horizontal axis represents the number of activated transmitting antennas, while the vertical axis indicates the system time consumption for processing a frame of data. The blue, black, and orange lines in the graph represent the time consumption of the proposed systems under different system clock speeds of 100 MHz, 200 MHz, and 300 MHz, respectively. As shown in Figure 11, the elapsed time required for processing a frame of data in both the conventional system and the proposed system increases as the number of virtual antennas grows. However, with an equivalent number of transmitting antenna channels, the proposed system demonstrates a processing speed enhancement of approximately 15% compared to the conventional system. Furthermore, we conducted experiments at three distinct system clock speeds. As illustrated in Figure 11, different colors represent the three clock speeds. The results indicate that the proposed system exhibits more pronounced real-time advantages at lower signal processing clock rates, achieving significant reductions in processing time. This performance enhancement underscores the system suitability for applications requiring high efficiency and speed in real-time signal processing environments.  
Figure 10: Storage resource consumption.