## 1 Introduction  
Today, the examination of technical conditions, photo- and video shooting of underwater cables, pipelines, and engineering structures is conducted via autonomous underwater vehicles (AUVs) along with traditional diving means; control and communication with AUVs are usually established through a hydroacoustic communication channel. One of the limiting factors for the characteristics of hydroacoustic communication is the underwater noise of natural and anthropogenic origins. It may be caused by water noise, seismic noise, flow noise, activities of the shipping industry, as well as activities of industrial and transportation enterprises located at the shelf, on the shore, and nearby the shore.  
For the appropriate consideration of influences of the underwater nonstationary noise on the characteristics of hydroacoustic communication systems, it is essential to obtain knowledge of its mathematical and physical models at time intervals that are comparable with durations of used signals throughout the connection session. The duration of a connection session with continuous exchange of information with an AUV can be several hours or longer.  
The distinctive peculiarity of the underwater noise that is observed in coastal areas with highly intensive shipping traffic is its prominent additional \"short-time\" nonstationarity; it becomes noticeable over time intervals that exceed a few dozen seconds. Therefore, it obstructs the forecasting of expected characteristics of the underwater noise, and consequently clouds the characteristics of hydroacoustic communication systems.  
The use of mean nonstationary noise characteristics at time intervals that exceed 30 s, as well as data that was received in other coastal water areas with similar hydroacoustic conditions, cannot always be justified from the physical point of view.  
Therefore, in order to evaluate the characteristics of hydroacoustic communication in a given water area, it appears viable to conduct long-term monitoring of underwater noise characteristics, accumulation, and generalization of statistical data.  
Moreover, underwater noise caused by shipping and industrial activities at the sea shelf may have a negative effect on marine species. A number of national and international documents include characteristics of underwater noise in the list of monitored characteristics of coastal territories [1; 2; 3]. Recommended methods of measuring the sea noise parameters are described in [2; 3; 4]. Noise monitoring can be conducted for various purposes; therefore, the controlled parameters should be chosen accordingly.  
For the purposes of underwater noise monitoring, specialized stationary systems (mounted to the sea floor and not intended for relocation), autonomous and drifting oceanological measuring systems that are intended for single use and multiuse, as well as the systems that are designed for taking measurements from the board of a moving or drifting vessel, can be used. In this case there are potential options of recording measurement information with built-in digital storage drives and/or life-stream of information via radio channel or cable.  
This research shows some of the pilot results of estimating the time variability of one-dimensional probability density function (1-D PDF) acoustic pressure sample values of underwater noise in the Peter the Great Bay, Sea of Japan, in the area east of the Primorsky aquarium, which is located on Russky Island, Russia. The method of histograms was used to evaluate PDFs. Knowing how the PDF of noise changes over time (for instance, when the vessel is passing by) allows more precise estimation of the likelihood ratio and implementation of the adaptive and robust signal detection algorithms.