# An Efficient Dynamic Engineering Implementation Architecture for MIMO Radar System
## 2 MIMO FMCW Radar Principle and System Analysis
### Double Storage Engineering Implementation Architecture for MIMO Radar Systems  
As shown in Figure 2, the widely used double storage MIMO radar system engineering implementation architecture in engineering applications consists of several key components: Range FFT, Range FFT data storage, Doppler FFT, Doppler data storage, target detection, and angle estimation. The specific process is as follows:  
**Step 1:** The Range FFT module obtains the digital IF signal from the analog-to-digital converter (ADC) sampler and performs Range FFT processing.  
**Step 2:** The data are stored in mass memory I. Since the data structure obtained from Range FFT is different from the input format for the subsequent Doppler FFT, the data need to be temporarily stored for dimension conversion and Doppler processing.  
**Step 3:** The Range FFT data stored in mass memory I are managed by the memory read/write control unit, which retrieves the data as needed and inputs them into the Doppler FFT module for processing, forming the complete Range-Doppler Matrix (RDM).  
**Step 4:** The RDM data are fully stored in mass memory II.  
**Step 5:** The target detection algorithm is executed to obtain the target's range and velocity information.  
Figure 1: MIMO radar virtual aperture expansion principle.  
**Step 6:** Based on the detected target's location (range, velocity), the system indexes and retrieves the corresponding antenna channel data from mass memory II, forming the target antenna data vector, which is then input into the angle estimation module [27].  
**Step 7:** Finally, the target's angle is estimated by executing the angle estimation algorithm.  
In the conventional double storage MIMO radar engineering implementation system, the radar data undergo two complete full-frame storage operations between two FFT processes. Assuming that the bit width of the radar data, denoted as \(W_{d}\), remains constant throughout the signal processing flow, the size of the storage resource \(S_{m}\) required for the two data storage operations can be expressed as follows:  
\[S_{m}=2W_{d}MKN_{a}, \tag{10}\]  
where \(M\) denotes the number of range sampling points, \(K\) signifies the number of velocity sampling points, and \(N_{a}\) represents the volume of virtual channel data.  
The total number of data read and write operations, \(A_{m1}\), for the two data stores is calculated as follows:  
\[A_{m1}=3 MKN_{a}, \tag{11}\]  
During the angle estimation phase, retrieving the data corresponding to each detected target across all virtual antenna channels from memory II is imperative. Let \(C\) represent the number of detected targets. The total number of data retrieval operations, denoted as \(A_{m2}\), can be calculated using the following equation:  
\[A_{m2}=CN_{a}, \tag{12}\]  
where \(N_{a}\) denotes the amount of virtual channel data.  
If the system uses a processing time unit of \(T\), where \(T\) represents the time required by the radar system to process a single data point, the processing time \(T_{s}\) for the entire system can be formulated as follows:  
\[T_{s}=(A_{m1}+A_{m2})T+T_{o}, \tag{13}\]  
where \(T_{o}\) is the algorithmic elapsed time outside the data stream.  
Figure 2: Double storage engineering implementation architecture for MIMO radar system.  
By combining Formulas (11) and (12), the processing time of the entire system can be derived, as presented in the following equation:  
\[T_{s}=(3 MKN_{a}+CN_{a})T+T_{o}, \tag{14}\]