## 3 Results
Nevertheless, neither checking for normality with significance level of 0.05 via application of the chi-square and Kolmogorov's criteria [11; 12; 13; 14] to the noise signal fragments that are shifting in time (30 min limit applies) nor changing accumulation time T from 0.1 s to 10 min have produced stable positive results. This could have been caused by ship traffic out of the line of sight, the anchorage, and the proximity of the port. Figure 5 shows lines of equal probability of the values of w(y): 0.000134 (red), 0.004432 (green), 0.053991 (blue), 0.1295 (cyan), 0.241971 (magenta), 0.3521 (yellow), 0.3867 (black); the values are  
Figure 3: Fragment of characteristics of the same signal (Figure 2, **top**). Top—oscillogram, bottom left—the signal fragment mean spectrum, bottom right—the signal initial fragment of the time correlation function. respective to the Figure 4. For the Gaussian distribution with the mean equal to 0 and variance equal to 1, this would be corresponding to the straight lines--also in accordance with values of y: \(\pm\)4, \(\pm\)3, \(\pm\)2, \(\pm\)1.5, \(\pm\)1, \(\pm\)0.5, \(\pm\)0.25 [14]. It is shown in Figure 5 that with this duration of signal fragments, the major deviations from the Gaussian distribution are observed in the areas with \(\mid\!y\!\mid\!<\!0.5\) (area of the most probable sample values) and \(\mid\!y\!\mid\!>\!3\) (area of the least probable sample values) [14]. With this accumulation time, no changes resulting from the passage of either the vessel or the motor boat were observed (710 s and 790 s, see Figure 1). Figure 4: Underwater noise signal after AGC and normalization by the level. Time dependence of the smoothed histograms for T = 10 s.  
Figure 5: Underwater noise signal after AGC and normalization by the level. Lines of equal probability for consecutive probability density function (PDF) for T = 10 s, see Figure 4. This is lines of equal probability of the values of w(y): 0.000134 (red), 0.004432 (green), 0.053991 (blue), 0.1295 (cyan), 0.241971 (magenta), 0.3521 (yellow), 0.3867 (black). For the Gaussian distribution with the mean equal to 0 and variance equal to 1, this would be corresponding to the straight lines—also in accordance with values of y: \(\pm\)4, \(\pm\)3, \(\pm\)2, \(\pm\)1.5, \(\pm\)1, \(\pm\)0.5, \(\pm\)0.25. Figure 6 shows the lines of equal probability for the same values w(y) that are seen in Figure 5, yet here the accumulation time T is equal to 1 s. No changes resulting from the passage of the vessel and the motor boat were observed (see Figure 1) with this accumulation time. The proper T value in order to detect change in PDF is determined in accordance with the set task. If the conditions of applicability of the central limit theorem are met, then with increase of T, the PDF comes close to the Gaussian distribution. The PDF for the nonstationary hydroacoustic noise in the shallow waters with intense shipping traffic may significantly differ from the Gaussian distribution, especially when vessels with distinct propeller cavitation are passing by the receiving system. Applicable to the tasks of detection of signals of final duration, the practical interest lies is estimation of PDF at the time intervals that correspond to the durations of the expected signals. When using \"long\" code words or \"line-by-line\" transmission of images via hydroacoustic communication channel, the proper T value can be anywhere from a fraction of a second to dozens of seconds. For comparison, Figures 7 and 8 show the lines of equal probability for low-frequency white Gaussian noise at the output of Bruel & Kjaer Sine Random Generator Type 1027 (Bruel & Kjaer, Naerum, Denmark). The noise was digitalized, filtered, normalized, and processed by the levels--in the same manner as earlier described underwater noise signal with the accumulation time of 10 s and 1 s, respectively.