## 3 SNR Evaluation Based on Proposed TP-CNN
### The Generation of UAV Remote Signal Dataset  
Before generating UAV remote signal dataset, the drone frequency hopping signal should first be generated. Frequency hopping communication system mainly includes a signal modulator, frequency synthesizer, and pseudo random (PN) code generator, where the PN code generator continuously and randomly generates PN code, and inputs it into \begin{table}
\begin{tabular}{c l} \hline \hline
**SNR Evaluation** & **Contribution** \\ \hline ML &
\begin{tabular}{l} Obtain the joint probability density function of the receiving channel \\ based on the probability density function of noise. \\ \end{tabular} \\ \hline M2M4 & Use the relation between variance and kurtosis to evaluate the SNR. \\ \hline ASS & Estimate noise power and signal power respectively to evaluate the SNR. \\ \hline CNN-LSTM & Evaluate SNR through the full connection layer that fuses the features. \\ \hline \hline \end{tabular}
\end{table} 
Table 1: The comparison of related signal-to-noise ratios (SNR) evaluation method. a frequency synthesizer to control the frequency generation. The transmitted signal is obtained by mixing the frequency generated by a frequency synthesizer with the baseband modulated signal, and the final mixing output signal is frequency-hopping signal, which is shown in Figure 1.  
To obtain the frequency hopping signal of UAV, Matlab is used for simulation modeling. Firstly, the baseband signal of the system is obtained by MSK modulation after using the 01 discrete signal generated randomly as the source bit. At the same time, carrier signals of different frequencies required by the frequency hopping communication system are generated. The hop frequency is 49, and the baseband signal is modulated with different carrier signals in each frequency hopping period. Then the drone frequency hopping signal is obtained. Finally, The signal passes through the small-scale flat fading Rayleigh channel and is, respectively, superimposed with noise with different signal-to-noise ratios of dB. Here, the superimposed noise has a 1 dB interval with the signal-to-noise ratio of the effective signal, starting at \(-10\) dB and ending at 10 dB. After down-sampling, the one-dimensional signal sequence dataset is obtained. The frequency hopping signal is denoted as:  
\[FH(t)=A\sum_{k=0}^{N-1}\omega_{\tau}(t-kT_{h})cos[2\pi f_{k}(t-kT_{h})+\varphi_ {n}], \tag{1}\]  
where \(N\) is the number of frequency points, \(A\) denotes the amplitude of signal, \(\omega_{\tau}\) represents a rectangular window of width \(T_{h}\), \(T_{h}\) is the period of a frequency hopping signal, \(f_{k}\) describes the set of frequency of drone hopping signal, \(\varphi\) denotes the initial phase and \(n=0,1,2,\ldots,N-1\). The expression of the signal after modulation is expressed as:  
\[S(t)=FH(t)m(t), \tag{2}\]  
where \(m(t)\) denotes the signal obtained after the original baseband signal data are modulated by the modulator, \(S(t)\) expresses the signal sent out by the transmitter. The definition of SNR is defined as:  
\[\text{SNR}=10 log(\frac{P(S(t))}{\sigma^{2}}), \tag{3}\]  
where \(P(. )\) denotes the operation of calculating the average power and \(\sigma^{2}\) signifies the variance of noise. After obtaining one-dimensional signal dataset, one-dimensional data need to be converted into two-dimensional data before inputting into neural network for training. The existing conversion methods mainly include Toplitz matrix, frequency waveform diagram and time waveform diagram. The time waveform diagram is applied to generate two-dimensional data in the paper. The time domain waveform diagram of a signal  
Figure 1: The generation of Unmanned Aerial Vehicles (UAV) remote signal dataset. represents the curve of the signal over time. The horizontal axis represents the order in time, and the vertical axis represents the amplitude of the signal at the current moment. Compared with frequency domain diagrams, the envelope of time domain diagrams can more easily show the energy or power characteristics of the signal.