## 3 MIMO Radar Simulation Platform
### Signal Receiving and Processing Module  
The signal receiving and processing module was mainly completed by a related algorithm in Matlab software. Firstly, the received signal needed to be down-converted from an RF signal to a baseband signal for analysis. In order to reduce the interference, two down-conversion processes were performed after the bandpass filters, which were used for filtering out other interferences introduced by the mixing. The CA-CFAR process eliminates the impact of false alarm probability and returns the target information. If the target is successfully detected, the return value is 1, otherwise it is 0. Finally, several repeated measurements were performed to obtain the average value of the target detection probability. The frequency conversion module is shown in Figure 7.  
The working flow of the frequency conversion module is as follows. The received signal went through two mixers to convert the signal to the middle frequency and the baseband frequency. Figure 6: Schematic diagram of a MIMO radar data-receiving module. In the data-receiving module, the received signal first passes the bandpass filter to filter out the clutter from the outside, then go through the digital receiver and the matched bandpass filters. Figure 7: Schematic diagram of the frequency conversion module. The frequency conversion module is composed of oscillator, bandpass filter, amplifier, and mixer. After each frequency conversion, the signal passed through the bandpass filter to filter out the interference signal and was then rectified through a power amplifier. The final output signal will be analyzed in next step. The structure of the upper and lower frequency conversion modules is basically the same. Since the received echo signals are mixed with various noise and disturbances in the time domain, the target will not be observed directly. It is necessary to switch the time domain signals into frequency domain signals to filter the interference of time domain noise and clutter. There are many kinds of system clutter, and the common probability density distributions include Weibull distribution, Rayleigh distribution, log-normal distribution, and \(K\) distribution. The expression of the Rayleigh distribution and the \(K\) distribution are shown in (18) and (4), respectively. The expressions for the Weibull distribution and the log-normal distribution are:  
\[f_{Weibull}(x;\lambda,k)=\frac{k}{\lambda}(\frac{x}{\lambda})\exp(-(\frac{x}{ \lambda})^{k}) \tag{19}\]  
\[f(x;\mu,\sigma)=\frac{1}{x\sigma\sqrt{2\pi}}\exp(-\frac{\left(\ln x-\mu\right) ^{2}}{2\sigma^{2}}) \tag{20}\]  
where \(\mu\) and \(\theta\) are the mean value and standard deviations of the normal distribution, respectively. \(\lambda\) and \(K\) are the scaling factor and the shape coefficient of Weibull distribution, respectively. When the Doppler frequency is 100 Hz, the frequency of the clutter sources and the pulse repetition are 10 GHz and 1 kHz, respectively. The power spectral density (PSD) obeys the Gaussian distribution, and the sampling rate of the system is 10 MHz. The scale factor, shape coefficient, and the variance of K distribution are all 1. The signal clutter is different for different power spectral densities. The general clutter power spectrum density includes Gaussian power spectrum, Cauchy power spectrum, all-pole power spectrum, and so on. In fact, the concept is generally used to measure the capacity of carrying the electromagnetic waves for every unit. In the dynamic target detection process, the Doppler shift of the received pulse radar signal can be obtained by FFT. \(F_{d}\) and \(f_{PRF}\) are the target Doppler shift and pulse repetition rate of the pulse radar, respectively. \(N\) and \(n\) are the sampling number and the serial number of the FFT process, respectively. \[F_{d}=\frac{f_{PRF}}{N}\times n \tag{21}\]  
It can be seen from (21) that the number of FFT sampling points affects the system accuracy of the Doppler frequency shift.