## 4 Proposed DoM Assessment Method
### Communication Performance Assessment  
For the BER analyses of various whistle patterns, computer simulations were executed under AWGN channel environments. For simplicity, assume that the whistle patterns were modeled as a linear function of \(at+b\). The length (\(L_{w}\)) of the tested whistles was fixed by 200 ms, the carrier frequency was set as 2 kHz, and four chirp rates (\(a\)) of 0 H/s, 1, 2.5, and 5 kHz/s were selected. Then, \(\Delta t\)s that satisfy the orthogonality requirements in Equation (6) with the given \(L_{w}\) and four chirp rates were calculated. The calculated whistle parameters were displayed in Table 3.  
Based on Table 3, the simulation parameters were set. \(L\)s were chosen as 20, 60, and 120, which were also used for the MOS tests. The Kasami sequences for the three sequence lengths were chosen for good autocorrelation performance [28; 29; 30]. Then, \(\Delta t\)s were selected 1, 2, and 5 ms to modulate the whistles. In this simulation, the 200 ms of \(\Delta t\) was excluded because when the \(\Delta t\) exceeded 200 ms, the misdetection by the overlap region did not exist, and the data rate was too low to be utilized as a communication system. The modulation indices of \(M\) and \(N\) were set as four each, and the total data rate was 20 bits/s. The BER results of the four chirp rate whistles of the proposed scheme and the conventional methods of Ref. [13] with three \(\Delta t\)s were shown in Figure 6.  
Figure 6: _Cont_. \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Parameter** & \multicolumn{4}{c}{**Values**} \\ \hline \(b\) (kHz) & \multicolumn{4}{c}{2} \\ \(a\) (kHz/s) & 0 & 1 & 2.5 & 5 \\ \(\Delta t\) (ms) & \(200\leq\Delta t\) & \(5\leq\Delta t\) & \(2\leq\Delta t\) & \(1\leq\Delta t\) \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Whistle parameters. In Figure 6a, for the 0 kHz chirp rate whistle, the BER of the conventional TFSK method did not decrease lower than 0.05, whereas that of the proposed scheme with a good correlation sequence (Kasami) decreases regardless of any \(\Delta t\). In Figure 6b, for the 1 kHz chirp rate whistle, the conventional TFSK in Ref. [13] showed the poor BER performance for the smaller \(\Delta t\) than 5 ms because the minimum \(\Delta t\) was calculated as 5 ms by Equation (6). In Figure 6c, for the 2.5 kHz chirp rate whistle, the conventional TFSK in Ref. [13] also showed poor BER performance with 1 ms of \(\Delta t\), which was smaller than 2 ms that was the minimum \(\Delta t\) calculated by Equation (6). However, the BERs of the proposed scheme were not affected for all \(\Delta t\)s. This result proved that the BER performance of the conventional TFSK in Ref. [13] depended on both the chirp rate and \(\Delta t\), whereas the proposed method kept on the good BER performance for any whistle pattern. In Figure 6a-d, when \(L\) was 20, the BER performance of the proposed method was good and similar to that of the larger \(L\)s.  
### Communication Performance Assessment  
In this subsection, the DoM experiments were conducted by the proposed assessment procedures of the modulated whistles in Section 3. The 1 st step of the proposed assessment was to find \(L_{c}\) that provides unrecognizable mimicking and determined the sequence length \(L\). In the 2 nd step, the assessment was executed for the DoM with the consecutive long-term whistles based on the obtained \(L\). For the 1 st step DoM assessment, various whistles were chosen from three species, i.e., White-sided dolphin, Delphinus delphi dolphin, Killer dolphin, from the Watkins marine mammal database [31]. Three whistles per species were chosen [31]. The whistle lengths of White-sided dolphin, Delphinus delphi dolphin, and Killer dolphin were about 0.3, 0.4, and 1.3 s, respectively. The spectrograms of the selected whistles are shown in Figure 7.  
Figure 6: Bit Error Rate (BER) in Additive White Gaussian Noise (AWGN) chirp-rate (_a_); (**a**) 0 Hz/s, (**b**) 1 kHz/s, (**c**) 2.5 kHz/s, (**d**) 5 kHz/s.