Shore Construction Detection by Automotive Radar for the Needs of Autonomous Surface Vehicle Navigation

Abstract

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.

Determining the Variability of the Territorial Sea Baseline on the Example of Waterbody Adjacent to the Municipal Beach in Gdynia

“…The baseline measurements performed by geodetic methods had many limitations, which included low coverage and duration. Therefore, the Authors recommend conducting bathymetric measurements in ultra-shallow waters by the hydrographic method, which involves the use of an unmanned surface vessel (a drone with a dozen centimetre draft) [48][49][50][51][52][53][54][55][56], on which a GNSS receiver and a Single Beam Echo Sounder (SBES) can be mounted. These measurement techniques enable high precision (1-5 cm (p = 0.95)) hydroacoustic surveys [57][58][59][60][61][62][63][64] performed during a relatively short time.…”

Methodology for Performing Territorial Sea Baseline Measurements in Selected Waterbodies of Poland

“…Performing classical hydrographic measurements with manned vessels might prove impossible due to the excessively large draft of the vessels and echo sounder transducers installed on their bows. Therefore, according to the authors it seems optimal to use USVs for baseline measurements [31][32][33][34][35][36]. An alternative method is the use of manned or unmanned aerial vehicles equipped with LiDAR to determine the baseline.…”

Geospatial Modeling of the Tombolo Phenomenon in Sopot using Integrated Geodetic and Hydrographic Measurement Methods

“…The predicted accuracy of this solution allows a depth accuracy of 2-5 cm root mean square (RMS) ( Figure 7a). An alternative solution to the use of a manned hydrographic vessel is the use of an unmanned surface vehicle (USV), which is increasingly used in bathymetric measurements [36][37][38]. The predicted accuracy of bathymetric measurements is identical to that of manned hydrographic measurements ( Figure 7b).…”