Bathymetry is a subset of hydrography, aimed at measuring the depth of waterbodies and waterways. Measurements are taken inter alia to detect natural obstacles or other navigational obstacles that endanger the safety of navigation, to examine the navigability conditions, anchorages, waterways and other commercial waterbodies, and to determine the parameters of the safe depth of waterbodies in the vicinity of ports, etc. Therefore, it is necessary to produce precise and reliable seabed maps, so that any hazards that may occur, particularly in shallow waterbodies, can be prevented, including the high dynamics of hydromorphological changes. This publication is aimed at developing a concept of an innovative autonomous unmanned system for bathymetric monitoring of shallow waterbodies. A bathymetric and topographic system will use autonomous unmanned aerial and surface vehicles to study the seabed relief in the littoral zone (even at depths of less than 1 m), in line with the requirements set out for the most stringent International Hydrographic Organization (IHO) order—exclusive. Unlike other existing solutions, the INNOBAT system will enable the coverage of the entire surveyed area with measurements, which will allow a comprehensive assessment of the hydrographic and navigation situation in the waterbody to be conducted.

Autonomous surface vehicles (ASVs) are becoming more and more popular for performing hydrographic and navigational tasks. One of the key aspects of autonomous navigation is the need to avoid collisions with other objects, including shore structures. During a mission, an ASV should be able to automatically detect obstacles and perform suitable maneuvers. This situation also arises in near-coastal areas, where shore structures like berths or moored vessels can be encountered. On the other hand, detection of coastal structures may also be helpful for berthing operations. An ASV can be launched and moored automatically only if it can detect obstacles in its vicinity. One commonly used method for target detection by ASVs involves the use of laser rangefinders. The main disadvantage of this approach is that such systems perform poorly in conditions with bad visibility, such as in fog or heavy rain. Therefore, alternative methods need to be sought. An innovative approach to this task is presented in this paper, which describes the use of automotive three-dimensional radar on a floating platform. The goal of the study was to assess target detection possibilities based on a comparison with photogrammetric images obtained by an unmanned aerial vehicle (UAV). The scenarios considered focused on analyzing the possibility of detecting shore structures like berths, wooden jetties, and small houses, as well as natural objects like trees or other kinds of vegetation. The recording from the radar was integrated into a single complex radar image of shore targets. It was then compared with an orthophotomap prepared from AUV camera pictures, as well as with a map based on traditional land surveys. The possibility and accuracy of detection for various types of shore structure were statistically assessed. The results show good potential for the proposed approach—in general, objects can be detected using the radar—although there is a need for development of further signal processing algorithms.

Hydrographic surveys, in accordance with the International Hydrographic Organization (IHO) S-44 standard, can be carried out in the following five orders: Exclusive, Special, 1a, 1b and 2, for which minimum accuracy requirements for the applied positioning system have been set out. They are as follows, respectively: 1, 2, 5, 5 and 20 m, with a confidence level of 95% in two-dimensional space. The Global Navigation Satellite System (GNSS) network solutions (accuracy: 2–3 cm (p = 0.95)) and the Differential Global Positioning System (DGPS) (accuracy: 1–2 m (p = 0.95)) are now commonly used positioning methods in hydrography. Due to the fact that a new order of hydrographic surveys has appeared in the IHO S-44 standard from 2020—Exclusive, looking at the current positioning accuracy of the DGPS system, it is not known whether it can be used in it. The aim of this article is to determine the usefulness of GNSS/Inertial Navigation Systems (INS) for hydrographic surveys. During the research, the following two INSs were used: Ekinox2-U and Ellipse-D by the SBG Systems, which were supported by DGPS and Real Time Kinematic (RTK) receivers. GNSS/INS measurements were carried out during the manoeuvring of the Autonomous/Unmanned Surface Vehicle (ASV/USV) named “HydroDron” on Kłodno lake in Zawory. The acquired data were processed using the mathematical model that allows us to assess whether any positioning system at a given point in time meets (or not) the accuracy requirements for each IHO order. The model was verified taking into account the historical and current test results of the DGPS and RTK systems. Tests have confirmed that the RTK system meets the requirements of all the IHO orders, even in situations where it is not functioning 100% properly. Moreover, it was proven that the DGPS system does not only meet the requirements provided for the most stringent IHO order, i.e., the Exclusive Order (horizontal position error ≤ 1 m (p = 0.95)). Statistical analyses showed that it was only a few centimetres away from meeting this criterion. Therefore, it can be expected that soon it will be used in all the IHO orders.

Autonomous navigation is an important task for unmanned vehicles operating both on the surface and underwater. A sophisticated solution for autonomous non-global navigational satellite system navigation is comparative (terrain reference) navigation. We present a method for fast processing of 3D multibeam sonar data to make depth area comparable with depth areas from bathymetric electronic navigational charts as source maps during comparative navigation. Recording the bottom of a channel, river, or lake with a 3D multibeam sonar data produces a large number of measuring points. A big dataset from 3D multibeam sonar is reduced in steps in almost real time. Usually, the whole data set from the results of a multibeam echo sounder results are processed. In this work, new methodology for processing of 3D multibeam sonar big data is proposed. This new method is based on the stepwise processing of the dataset with 3D models and isoline maps generation. For faster products generation we used the optimum dataset method which has been modified for the purposes of bathymetric data processing. The approach enables detailed examination of the bottom of bodies of water and makes it possible to capture major changes. In addition, the method can detect objects on the bottom, which should be eliminated during the construction of the 3D model. We create and combine partial 3D models based on reduced sets to inspect the bottom of water reservoirs in detail. Analyses were conducted for original and reduced datasets. For both cases, 3D models were generated in variants with and without overlays between them. Tests show, that models generated from reduced dataset are more useful, due to the fact, that there are significant elements of the measured area that become much more visible, and they can be used in comparative navigation. In fragmentary processing of the data, the aspect of present or lack of the overlay between generated models did not relevantly influence the accuracy of its height, however, the time of models generation was shorter for variants without overlay.

Hydrographic surveys enable the acquisition and processing of bathymetric data, which after being plotted onto nautical charts, can help to ensure safety of navigation, monitor changes in the coastal zone, and assess hydro-engineering structure conditions. This study involves the measurement of waterbody depth, identification of the seabed shape and geomorphology, the coastline course, and the location of underwater obstacles. Hydroacoustic systems mounted on vessels are commonly used in bathymetric measurements. However, there is also an increasing use of Unmanned Aerial Vehicles (UAV) that can employ sensors such as LiDAR (Light Detection And Ranging) or cameras previously not applied in hydrography. Current systems based on photogrammetric and remote sensing methods enable the determination of shallow waterbody depth with no human intervention and, thus, significantly reduce the duration of measurements, especially when surveying large waterbodies. The aim of this publication is to present and compare methods for determining shallow waterbody depths based on an analysis of images taken by UAVs. The perspective demonstrates that photogrammetric techniques based on the SfM (Structure-from-Motion) and MVS (Multi-View Stereo) method allow high accuracies of depth measurements to be obtained. Errors due to the phenomenon of water-wave refraction remain the main limitation of these techniques. It was also proven that image processing based on the SfM-MVS method can be effectively combined with other measurement methods that enable the experimental determination of the parameters of signal propagation in water. The publication also points out that the Lyzenga, Satellite-Derived Bathymetry (SDB), and Stumpf methods allow satisfactory depth measurement results to be obtained. However, they require further testing, as do methods using the optical wave propagation properties.

The integration of geospatial data in hydrography, performed using different measurement systems, involves combining several study results to provide a comprehensive analysis. Each of the hydroacoustic and optoelectronic systems is characterised by a different spatial reference system and the method for technical implementation of the measurement. Therefore, the integration of hydrographic data requires that problems in selected fields of electronics, geodesy and physics (acoustics and optics) be solved. The aim of this review is to present selected fusion methods applying the data derived from Global Navigation Satellite System (GNSS), Real Time Kinematic (RTK) measurements, hydrographic surveys, a photogrammetric pass using unmanned vehicles and Terrestrial Laser Scanning (TLS) and compare their accuracy. An additional goal is the evalution of data integration methods according to the International Hydrographic Organization (IHO) S-44 standard. The publication is supplemented by implementation examples of the integration of geospatial data in the Geographic Information System (GIS). The methods described indicate the lack of a uniform methodology for data fusion due to differences in both the spatial reference systems and the techniques used. However, the integration of hydroacoustic and optoelectronic data allows for high accuracy geospatial data to be obtained. This is confirmed by the methods cited, in which the accuracy of integrated geospatial data was in the order of several centimetres.