# An Efficient Dynamic Engineering Implementation Architecture for MIMO Radar System
## 5 Results
### Compatibility of Different Arrays  
Utilizing a one-dimensional antenna array I and a two-dimensional planar antenna array II, the performance of the proposed system is validated for both planar detection and three-dimensional spatial detection. We transfer 10 frames of data from the processing results to a computer via a network port. We analyze the detection performance of the real-time radar signal processing system using MATLAB R2021 bTo validate the system's output, we simultaneously use real-time kinematic(RTK) system to measure the target's position in real-time and synchronize these measurements with the radar data based on timestamps. As shown in Figure 12a, the black circles represent the RTK-derived positions corresponding to each radar data point, serving as the reference. The colored trajectories represent radar outputs from different data frames. Due to the large reflective surface of the target, multiple points are detected in each frame. Figure 11: System processing time. Figure 12: Target trajectory. (**a**) Comparison of radar and RTK output results. (**b**) Difference between radar and RTK output results. Figure 12b illustrates the error curve between the radar measurement points and the reference positions. For each frame, the error is calculated as the average distance between all radar measurement points and the reference position. As shown in the figure, the radar-derived trajectory closely matches the reference trajectory, with the average positional error of the radar output points in each frame not exceeding 1.2 m. Therefore, the radar output points accurately represent the actual motion trajectory of the target. Figure 13a,b display the output results after signal acquisition and real-time processing for the conventional system and the proposed system, respectively. The horizontal axis represents the horizontal position of the target, the vertical axis represents the longitudinal distance of the target, and target traces from the same data frame are denoted by identical colors. Notably, when employing RF board I, while the motion of the target introduces variations across different data frames, the overall results exhibit a high degree of similarity for the same radar system. The signal processing system can detect and output 3-5 point cloud data values per frame for a single target vehicle traveling on an actual road. By aggregating data from multiple frames, the output results of the radar system consistently align with the exact motion trajectory of the target. Figure 13a,b present the output results from the conventional system (DS-MRS) and the proposed system (ED-MRS), respectively. The horizontal axis represents the horizontal position of the target, the vertical axis represents the longitudinal distance of the target, and the third axis (z-axis) represents the height information of the target, while target traces from the same data frame are denoted by identical colors. When utilizing RF board II, in contrast to the results obtained with the RF board I, the system can acquire information about the vertical orientation of the target. A comparative analysis of the results from the different systems indicates that the proposed system can produce detection results that are consistent with the actual motion of the target. Moreover, it achieves functionality comparable to that of a conventional radar system in one-dimensional planar and two-dimensional spatial detection scenarios. Figure 13: Antenna array I processing results. (**a**) DS-MRS antenna array I target trajectory. (**b**) ED-MRS antenna array I target trajectory. To comprehensively assess the compatibility and stability performance of the proposed engineering system across different antenna arrays, we processed 10 consecutive frames of data from both antenna array I and antenna array II. We recorded the time that the system took to process each frame and conducted a detailed analysis.