Article citation information:
Korban, D.,
Melnyk, O., Onishchenko, O., Kurdiuk, S., Shevchenko, V. Obniavko, T.
Radar-based detection and recognition methodology of autonomous surface vehicles
in challenging marine environment. Scientific Journal of Silesian
University of Technology. Series Transport. 2024, 122, 111-127. ISSN: 0209-3324. DOI: https://doi.org/10.20858/sjsutst.2024.122.7.
Dmytro KORBAN[1],
Oleksiy MELNYK[2], Oleg ONISHCHENKO[3], Serhii KURDIUK[4],
Valerii SHEVCHENKO[5],
Tatyana OBNIAVKO[6]
RADAR-BASED DETECTION AND RECOGNITION METHODOLOGY OF AUTONOMOUS SURFACE
VEHICLES IN CHALLENGING MARINE ENVIRONMENT
Summary. This
paper presents a methodology that combines radar polarization selection and
recognition techniques for navigating objects in atmospheric formations, with a
special focus on unmanned surface vehicles (ASVs). The proposed technique
utilizes the concept of an energy dissipation matrix to represent these objects
as characteristic “shiny dots”. By strategically changing the
polarization of the emitted and received electromagnetic waves, the resulting
echo energy dissipation matrix is determined. This approach allows the
formation of an intensity-based repository of atmospheric formations,
which gives SRPC a complete set of tools to account for atmospheric conditions
in radar identification of remote objects, including ASVs. The practical
application of this technique extends to the improvement of a distinct class of
shipborne radar systems optimized for ASVs and their specific navigation
requirements. Ultimately, this technology bridges the gap between advanced
radar technology and the emerging field of unmanned ground vehicles, providing
safer and more proficient navigation in challenging weather conditions.
Keywords: autonomous
surface vehicles, object detection and ranging, radar technology, adverse
weather conditions, atmospheric interference, environmental factors, signal
characteristics, vessel particulars, sensor performance, adaptability,
shipping, navigation, influence factors, detection accuracy
1.
INTRODUCTION
Autonomous
Surface Vehicles (ASVs) are unmanned or remote-controlled waterborne vehicles
designed to operate on the surface of bodies of water without human
intervention. These vehicles play a crucial role in various maritime
applications, including environmental monitoring, oceanographic research,
surveillance, security, and even maritime transportation. ASVs can vary in size
and capabilities, ranging from small, compact units to larger vessels equipped
with advanced sensors, communication systems, and navigation technologies and
offer a compelling array of benefits for maritime operations. Their deployment
enhances safety by tackling hazardous tasks without risking human lives, while
also yielding cost efficiencies through reduced crew-related expenses. ASVs
enable continuous and adaptable data collection, facilitating remote monitoring
and research in otherwise inaccessible areas.
The literature
review on the research topic included a comprehensive study of radar
technologies and their application in maritime environments. Various aspects of
radar systems [1], focuses on active phase-discharge antenna
arrays. A monograph [2]
covering various aspects of antenna systems. Methods
and algorithms of information processing under interference conditions [3]
considers multi-position radar systems. Authors in
[4] discuss the impact of turbulence on radio wave polarization angle.
The functionality and applications in challenging atmospheric and environmental
conditions presents mathematical and statistical details related to radar
modeling, particularly for stacked radar objects [5,6] are discussed. Topics
such as antenna arrays and methods to enhance environmental monitoring along
maritime routes using remote sensing explored in [7], the design, operation,
and applications of radar systems on board ships [8]. The article [9]
investigates the invisibility functions of two radiometric complexes and the
technical aspects of radiometric systems, with a special focus on the analysis
of invisibility. The article [10] explores the challenges and considerations
when using radio technical systems of the Ukrainian Air Force in adverse
weather conditions and during natural meteorological events.
The
manual [11] dedicated to radar, AIS
(Automatic Identification System), and target tracking for marine radar users. It
covers radar principles, AIS, and techniques for tracking targets, making it a
valuable resource for marine radar operators. The book [12]
discusses the polarization of radio waves and the polarization structure of
radar signals, and covers the theory and practical aspects of radio wave
polarization in radar systems. The paper [13] explores radar recognition of
navigation objects based on the polarization parameters of electromagnetic
waves, mathematical and technical aspects of radar recognition of navigation
objects from polarization data are considered. In thesis [14] analysis of
functional relationships between a navigation object and its environment,
concerning the operation of a ship's radar station considered including the
findings related to radar systems and their interactions with the ship's surroundings.
Matrix of radar information channel propagation during radar observation of
navigational objects researched in [15]. The paper [16] presents a lightweight
radar ship detection framework with hybrid attentions and discusses the
development of a ship detection system using radar data with a focus on
attention mechanisms. In [17] introduced a novel approach for estimating ship
speed and heading using radar sequential images, methodology and algorithms for
ship speed and heading estimation based on radar data. The research [18] deals
with inshore ship detection using multi-modality saliency analysis for
synthetic aperture radar (SAR) images. The articles [19, 20] present a network
for detecting small ships in synthetic aperture radar (SAR) imagery while
considering sidelobes and focuses on ship detection in synthetic aperture radar
(SAR) images using the YOLO-SARshipNet approach. In
[21], methods for estimating ship parking parameters using Multi-LiDAR and MMV
radar data fusion are discussed, in [22] beamforming using LOFAR radio
telescopes for passive radar applications is investigated, and in [23]
Cassegrain-type antennas used in radio telescopes, focusing on development and
applications, making collective contributions to ship navigation, radio telescope
technology, and antenna design knowledge studied. In [24,25] a multi-criteria
approach focused on optimizing the composition of technical means is considered
and a model for the structure of project portfolios is investigated. Paper [26]
outlines the current state of the art of wired MSAs and describes their
designs, types, benefits, and specific impacts in MSC systems, ships’
electric propulsion systems operation on curvilinear trajectory studied in
[27].
In
today's maritime environment, characterized by an increasing number of ASVs,
there is scientific uncertainty about the effectiveness and reliability of
radar surveillance by shipboard radar systems. Such a problem arises due to the
complex conditions of the marine environment, including atmospheric influences
such as sea state, rain snow, hail, etc., which can distort radar signals and
make it difficult to detect ASVs. Moreover, the variety of ASV configurations
and sizes can cause variable radio signatures, making identification and
tracking more difficult. Thus, there is a need for research and development of
technical solutions to improve the reliability and accuracy of ASV surveillance
by shipboard radars, considering the diverse atmospheric and marine environment
effects as well as ASV characteristics.
This
scientific challenge emphasizes the need for research and innovation to improve
surveillance of autonomous surface vehicles using shipborne radar systems, and
guides the development of new methods and technologies to overcome the
challenges associated with detecting and monitoring ASVs in various maritime
environments.
2. MATERIALS
AND METHODS
The
development of a technique that combines the methods of selection and
recognition of radar polarization for surface objects in dense atmospheric formations
with special emphasis on ASVs is an urgent task, so the proposed technique uses
the concept of energy dissipation matrix to represent these objects in the form
of characteristic “shining points”. By strategically changing the
polarization of emitted and received electromagnetic waves, the resulting
echo-signal energy dissipation matrix is determined.
This
research task focuses solely on radar systems (radar) for surveillance of ASVs
which are driven by the desire to better understand and improve the detection,
monitoring and tracking processes of ASVs in variable marine and atmospheric
environments. The problem is focused on analyzing and improving the radio
signatures of ASVs and optimizing radar systems for their effective detection,
while ASVs, while significant, and are focused on the transmission of vessel
information, which is beyond the scope of this research problem. The
representation of factors influencing detection of
ASVs in challenging weather conditions (Tab.1):
Tab. 1
The factors influencing detection of surface objects
in challenging weather conditions
|
Factors |
Weather
conditions |
Impact
on radar performance |
|
Atmospheric Conditions and Interference |
Rain and Snow |
Weaken radar
signals, create additional reflections |
|
Fog and Mist |
Scatter
radio waves, reduce visibility |
|
|
Wind and Storm |
Alter vessel
trajectories, impact on detection accuracy |
|
|
Environmental factors and dynamics of the
marine environment |
Sea Waves |
High waves
cause multiple reflections, hinder signal accuracy |
|
Sea Spray |
Creates
additional radar reflections, affects target separation |
|
|
Icing |
Increases
radar cross-section, alters vessel characteristics |
|
|
Radar and Signal Characteristics |
Frequency Choice |
Different
frequencies react differently to conditions |
|
Disorder and noise |
Electromagnetic
interference affects signal quality |
|
|
Sea Clutter |
Reflections
from sea surface and objects, obscures targets |
|
|
Vessel Characteristics and Particulars |
Hull shape |
Complex
shapes hinder accurate radar readings |
|
Hull Material |
Different
materials scatter radio waves differently |
|
|
Principal Dimensions and Motion Parameters |
Impact
target's radar cross-section |
|
|
Sensor Performance and Adaptability |
Adaptive Algorithms |
Respond to
changing conditions for accurate readings |
|
Noise Suppression |
Techniques
to mitigate electromagnetic interference |
|
|
Signal Processing |
Extract
valid signals from noise and interference |
This
schematic visually represents the various factors that can affect the detection
of ASVs in challenging weather conditions. Each section highlights a specific
factor and its influence on the effectiveness of radar-based detection for
ASVs.
Fig.1. Ship radar station and detection zones
The
histogram in Fig. 2 illustrates the influence of various factors on the detection
of ASVs in complex maritime environments. The factors are categorized and
listed along the vertical axis, while the horizontal axis represents the impact
score on a scale of one to ten, where (1) represents minimal impact and (10)
represents significant impact, and serves to visually display the varying
degree of impact of each factor on ASV detection, providing insight into
optimizing detection strategies in adverse marine environment:
·
Atmospheric Conditions and Interference factor,
ranked with a high influence rating of (8), highlights the impact of
atmospheric phenomena and interference, such as rain, fog, and wind, on ASV
detection accuracy.
·
Environmental Factors and Marine Dynamics with a
rating of (7) emphasizes the relevance of environmental conditions like sea
state, water spray, and marine icing in affecting ASV detection.
·
Radar and Signal Characteristics (9) factor
holds substantial influence with a rating of 9, underscoring the role of radar
system parameters and signal characteristics in determining ASV detectability.
·
Vessel Particulars factor assigned a rating of
(5) indicates the moderate impact of vessel-specific characteristics, including
size, shape, and materials, on ASV detection performance.
·
Sensor Performance and Adaptability factor with
a rating of (6) underscores the influence of sensor performance and
adaptability, including the ability to process signals and adjust to changing
conditions, on ASV detection reliability.
The
above scheme highlights key factors affecting the detection of ASV in
challenging weather conditions. Atmospheric factors such as rain, fog, and
strong winds can hinder visibility and signal strength. Environmental dynamics,
including high waves and marine icing, may influence target detection and cause
reflections. Radar characteristics such as frequency choice and clutter
influence signal quality and background noise. Vessel traits like shape and
material influence radar cross-section. Sensor adaptability and noise
suppression techniques are essential for accurate ASV detection. These insights
emphasize the need for comprehensive considerations when detecting ASVs in
adverse marine environments.
Fig.2. Influence of various factors on the detection of ASVs
Spatial
and temporal filtering of interference can be performed by ship radar
polarization complexes (SRPC) having different types of antennas, including
phased antenna arrays. SRPC receiver simultaneously receives echo signals from
navigational object and atmospheric formation (complex object). The echo
signals of the atmospheric formation obscure the echo signals of the navigation
object observed by the SRPC. Hydrometeor particles of the atmospheric formation
are dipole reflectors for the emitting antenna SRPC of the centimeter wave
length diapason (3-10 cm) and have a length equal to λ/2 with an average
effective dipole scattering surface
The
effectiveness of radar observation of a navigation object, located in the area
of the atmospheric formation, will be if the total effective scattering surface
of the particles of the atmospheric formation is less than the effective
scattering surface of the navigation object by the value of the suppression
coefficient N, i.e.
where
However,
real
Various
interference suppression methods and devices have now been developed, including
upper-pass and lower-pass filter systems, band-pass filters, angle selection
and blanking devices, pulse repetition frequency discriminators, frequency
hopping, side-lobe compensators, etc. However, uncertainties caused by
interference lead to erroneous, relative to the real situation, decisions. The
different situations available for radar observation of navigational objects
make it necessary to take into account the semantics and pragmatics of the echo
signals of the atmospheric interference. This necessitates the use of a
thesaurus, which forms the information about the atmospheric interference
(intensity of the precipitation). The characteristics of the echo signals
during radar observation of a navigation object in atmospheric interference are
based on temporal, spatial and polarization parameters. The polarization actual
Stokes parameters allow the object recognition on the background of atmospheric
interference using the thesaurus available in the SRPC archive by comparing the
echo signals of the navigation object with the echo signals from precipitation
of known intensity. The simulation model in this case is an energy scattering
matrix with the elements represented by the actual Stokes energy parameters,
which are easily measured by SRPC. The polarization direction of atmospheric
interference compensation in radar observation of navigation objects is an
alternative solution to the existing problem [13-15].
Obtaining
and use of energy scattering matrix for suppression of atmospheric interference
in radar observation of navigational objects is a current concern in shipborne
radiolocation.
Remote
measuring of time-averaged polarization parameters of Stokes echo signalsS1, S2, S3,
S4 of partially polarized wave during radar observation of
navigation objects located in the zone of atmospheric formation was carried out
in linear (L) and circular (CR) bases. When using linear basis, the
relationship between Stokes parameters and amplitudes of orthogonal
electromagnetic wave components Ехmax,
Еуmax
and phase difference Fху
between them is established using the following relations:
Using
a circular basis, the relationship between Stokes parameters and the amplitudes
of the orthogonal right ERmax
and left ELmax
rotation components of the electric wave vector and the phase difference
between them FRL is
written in the form:
The
totality of Stokes parameters of electromagnetic wave echo signals of the
observed SRPC navigation object at each considered moment of time reflects its
functioning. The use of linear and circular bases is considered in terms of the
value of the information obtained when observing a navigational object.
Let
us introduce the Stokes vector parameter for the quasimonochromatic wave
emitted by the SRPC antenna as grouped Stokes parameters in a 4x4
vector-column:
A
navigation object observed by SRPC is sequentially irradiated by an
electromagnetic wave of four polarizations, of which three are linear vertical
(LV), linear horizontal (LH) and with the electric vector
inclined at 45o (L45o)
and one circular (CR) of right or
left direction of rotation of the electric vector. The Stokes vector for each
polarization of the emitted wave is written by the following relations:
When
an irradiating wave of any of the four polarizations listed above is scattered
on a navigation object, an atmospheric formation or a navigation object and an
atmospheric formation (complex object), an echo signal of a certain
polarization is formed, carrying information about their reflecting properties.
The Stokes parameters of the irradiating wave undergo changes during reflection,
since the reflected electromagnetic wave in both cases has a polarization
structure different from the polarization of the irradiating wave. The
reflection coefficients also change. Due to the linearity of the
electromagnetic wave scattering process, the relationship between the
polarization parameters of the reflected wave and the reflection coefficients
for each of the given polarizations of the irradiated wave are generally
determined by a relation consisting of three matrices, where the elements of the
first and third matrices represent the Stokes parameters of the radiated and
reflected waves, and the elements of the second matrix characterize the
reflective properties of the complex object of radar surveillance SRNS:
As
a result of irradiation of a complex object with electromagnetic waves of four
fixed polarizations, all elements α11...α44 of
matrix (7), which are the actual Stokes energy parameters forming the energy
scattering matrix of the complex object (CO) and fully characterizing its
reflecting properties, i.e.
All
elements included in the energy dissipation matrix (8) of a complex object are
easily measured by SRPC on the ship's route. The energy dissipation matrix
solves the problem of polarization selection of the navigation object located
in the zone of dangerous atmospheric formation. Separation of echo-signals of a
navigation object and an atmospheric formation is performed by the difference
of their energy scattering matrices by subtracting from the energy matrix of a
complex object the energy matrix of an atmospheric formation, which for known
types of dangerous atmospheric formations (precipitation of different
intensity) is located in the computer archive of SRNS. Most real atmospheric
media have electrodynamic parameters corresponding to the real and symmetric
energy dissipation matrix. Stokes parameters are measured in one-dimensional
radar channels in the absence of physical and geometric boundaries of the radar
volume of the atmospheric formation. Stokes parameters are measured in
one-dimensional radar channels in the absence of physical and geometric
boundaries of the radar volume of the atmospheric formation. According to the
selected irradiated and reflected signals from the navigation object and
atmospheric formation, the structure of the energy matrix of scattering of the
complex object is determined, which makes it possible to relate the Stokes
parameters of the complex object with radar signals and, ultimately, to ensure
the operation of SRNS in a complex atmospheric environment when solving the problem
of polarization selection.
3. RESULTS AND DISCUSSION
The energy matrix of the
atmospheric formation is related to the concept of thesaurus, i.e., the
accumulated information about the structure of the atmospheric formation and
the processes occurring in it. Radar cumulative processing of measured actual
Stokes parameters of echo-signals of partially polarized waves of a complex
object allows us to apply its energy matrix of scattering to separate the
echo-signal of a navigation object from the echo-signal of a complex object.
In order to solve the problem,
the echo signal of the navigation object is separated from the echo signal of
the complex object by using two
energy matrices
The SRPC measures the atmospheric
formation Stokes parameters for the precipitation intensities that may be
encountered on the ship's route, including the precipitation intensities
presented in Table 2. From the radar measurements of the SRPC Stokes
parameters, energy scattering matrices of precipitation are compiled for each
intensity. Using the measured first Stokes parameter the echo signal of the
complex object, the intensity of the precipitation on the ship's route is
determined, which is entered into the search program atmospheric formation
energy matrix of the measured intensity.
Tab.
2.
Radar reflectivity of
precipitation (z) as
a function of intensity of precipitation (I)
|
I, mm/h |
z, dB |
|||||||
|
1 |
2 |
3 |
4 |
5 |
6 |
7 |
8 |
|
|
1 |
23,0 |
24,4 |
23,1 |
23,6 |
- |
22,6 |
- |
- |
|
5 |
34,2 |
34,2 |
35,0 |
34,1 |
34,7 |
35,4 |
35,1 |
- |
|
10 |
39,0 |
38,4 |
40,1 |
38,6 |
38,9 |
41,3 |
40,7 |
33,4 |
|
15 |
41,1 |
42,1 |
43,0 |
40,1 |
40,1 |
45,2 |
42,4 |
36,1 |
|
25 |
45,0 |
45,2 |
46,0 |
45,0 |
45,2 |
49,1 |
47,3 |
39,2 |
|
50 |
50,2 |
48,3 |
52,0 |
49,1 |
48,7 |
54,4 |
53,9 |
44,6 |
|
100 |
55,0 |
52,4 |
57,1 |
53,6 |
52,9 |
60,0 |
59,5 |
49,4 |
|
150 |
57,9 |
54,8 |
60,2 |
56,3 |
55,4 |
63,4 |
62,9 |
52,2 |
The devices (Fig. 3 and Fig. 4)
automatically subtract from the energy matrix of the echo-signal of the complex
object the energy matrix of the atmospheric formation by precipitation of the
measured intensity at the moment of radar observation of the complex object.
The energy matrix of the navigational object obtained as a result of
subtraction is fed to the SRNS indicator and computer display for remote
observation of the navigational object located in the zone of dangerous atmospheric
formation on the ship's route.
Stokes parameters of the CO echo
signal when it is irradiated by electromagnetic waves of four polarizations:
So, for liquid precipitation of
intensity I = 25 mm/h their energy scattering matrix of the echo signal partially polarized
wave has the following values of its elements (Stokes parameters):
Fig. 3. Functional scheme of SRPC
device synthesizing algorithm for solving the polarization selection problem of
navigation object located in the zone of dangerous atmospheric formation:
Where: 1 - SRPC computer display;
2,3 - DC amplifiers; 4,12,13 - phase-shifter amplifiers; 5,6 - multiplication
stages; 7,8 - paraphase amplifiers; 9 - SRPC display; 10,11 - quadrature
detectors; 14,15,19,22 - line amplifiers for 4 MHz intermediate frequency;
16,17 - heterodynes for 4 MHz and 30 MHz intermediate frequency;18 - SRPC
transmitter; 20,21 - balance mixers for 4 MHz intermediate frequency; 23 - circulator;
24,25 - 30MHz intermediate frequency amplifiers; 26 - power divider; 27,30 -
30MHz intermediate frequency balanced mixers; 28,29 - phase shifters; 31,34 -
high frequency signal amplifiers; 32,33 - attenuators; 35,39 - receiver
protection arresters; 36,38 - antenna switches; 37 - polarization selector; 40
- transmitter
The energy scattering matrix of
the complex object echo signal has the following value of elements:
(11)
Fig. 4. Functional
scheme of the device for obtaining the energy scattering matrix of the complex
object echo signal (CO) l11-l44
- the elements of the CO energy scattering matrix; 1 - RLT - D6386 ultrasonic
delay lines; 2, 3, 4 - summing and subtraction blocks; 5 - energy scattering
matrix of the complex object echo signal
Then the energy scattering matrix
of the navigational object echo signal determined as the difference and written
in the form:
(12)
When the intensity of liquid
precipitation I = 10 mm/h, the energy scattering matrix of
the atmospheric formation has the following values of its elements:
(13)
The energy scattering matrix of
the echo signals of the complex object
(14)
The energy scattering matrix of
the echo signals of the navigation object
(15)
At air temperatures of less than
-2oC, snowfall intensity
is determined by three gradations: weak (I
= 0,02 - 0,10 mm/h), moderate (I = 0,11 - 1,00 mm/h) and strong (I >
1,00 mm/h). The energy scattering
matrix of the snowfall echo signals
(16)
The energy scattering matrix of
the echo signals of the complex object
(17)
The energy scattering matrix of
the echo signals of the navigation object
(18)
The obtained matrix of energy
dissipation of echo-signals of a navigation object corresponds to its
representation in the form of a set of “shining points”, to a
certain choice of polarizations of the electromagnetic wave irradiating the
navigation object, and to the received echo-signals of vertical and horizontal
polarizations.
The advantage of the considered
method of radar polarization selection for a navigation object located in the
zone of a dangerous atmospheric formation is the accumulation of meteorological
information on reflective properties of existing dangerous atmospheric
formations, which is entered into the SRNS data bank. The task of SRPC is to
measure actual parameters of Stokes echo-signals from a complex object on the
ship's route, by which the intensity of the process in the atmospheric
formation (intensity of rain or snowfall) is determined and on the basis of the
available thesaurus the measured intensity of a dangerous atmospheric formation
is compared with the existing ones in the SRPC data bank. For the measured
intensity in the SRPC data bank, the energy dissipation matrix of the observed
hazardous atmospheric formation is automatically found. From the energy
dissipation matrix of the complex object obtained by the SRPC shaper (Fig. 3
and Fig. 4), the energy dissipation matrix of the hazardous atmospheric
formation is subtracted. When subtracting from the atmospheric formation energy
dissipation matrix the complex object energy dissipation matrix, the navigation
object energy dissipation matrix is obtained, which is fed to the display and
indicator of the SRPC computer for its remote radar observation. Taking into
account the separation of the echo-signal of the atmospheric formation and the
echo-signal of the complex object by their energy dissipation matrices and
obtaining the energy dissipation matrix of the navigation object, the formed
thesaurus of atmospheric formations of certain intensities allows SRPC to
effectively use the accumulated information about the atmospheric formation and
to fully consider the factors of the atmospheric environment during radar
recognition of remote objects of observation.
The results obtained, which are
methodological in nature, can be further embodied in the task of unifying the
procedures for improving a ship radar complex of a certain type and its
functional capabilities, and the practical usefulness of the considered
methodology for recognizing navigational objects located in the zone of
dangerous atmospheric formation is aimed at the application of program-target
methodology of detection, selection, and recognition of navigational objects.
When implementing the algorithm
of radar detection and polarization selection of navigation objects, the main
element of the SRNS structure is a radar antenna, which implements the
algorithm of radar detection and polarization selection of a navigation object
according to its energy dissipation matrix. In solving this problem, an
omnipolarized antenna, which is a polarization analyzer, is used to control the
amplitude, phase, and polarization of the radiated electromagnetic wave.
The practical application of this
technique extends to the improvement of a distinct class of ship radar systems
optimized for ASV detection and their special navigational requirements. The
deployment of the radar detection and polarization selection algorithm for
navigational objects takes place around the SRPC radar antenna, which plays a
central role in the implementation of the radar detection and polarization
selection algorithm using an energy dissipation matrix. In addition, the
integration of an omnipolarized antenna acting as a polarization analyzer
allows precise control of the basic properties of electromagnetic waves,
including amplitude, phase, and polarization.
4. CONCLUSION
This
study emphasizes the importance of using the energy scattering matrix of
complex objects to solve the difficult problem of polarization selection of
navigation objects in complex atmospheric conditions on seaways. The effective
use of real Stokes polarization parameters embedded in the energy scattering
matrix of complex objects observed with SRPC provides a robust methodology.
This methodology allows efficient separation of echo signals from navigational
objects and complex entities, even under varying degrees of atmospheric
interference. Characteristically, this innovation is equally applicable to
autonomous surface vehicles, extending further to underwater vehicles. Due to
the effective separation of radar echo signals from ASVs and their environment,
including complex atmospheric interference, the technique can improve the
accuracy and efficiency of radar-guided navigation for both surface and
underwater autonomous vehicles. The research not only proposes the solution for
radar echo separation, but also demonstrates its ability to improve radar
navigation performance under various atmospheric phenomena. This is a notable
step towards enhancing navigational safety and situational awareness on
maritime routes, covering both surface and underwater environments.
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Received 16.12.2023; accepted in
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Scientific Journal of Silesian University of Technology. Series
Transport is licensed under a Creative Commons Attribution 4.0
International License
[1]
Department of Ship Handling, National University “Odessa Maritime
Academy”, 8, Didrikhson Str., Odesa, 65052, Ukraine. Email:
korbandmv@gmail.com. ORCID: https://orcid.org/ 0000-0002-6798-2526
[2]
Department of Navigation and Maritime Safety, Odesa National Maritime
University, 34, Mechnikov Str., Odesa, 65029, Ukraine. Email:m.onmu@ukr.net.
ORCID: https://orcid.org/ 0000-0001-9228-8459
[3]
Department of Technical Fleet Operation, National University “Odessa
Maritime Academy”, 8, Didrikhson Str., Odesa, 65052, Ukraine. Email:
oleganaton@gmail.com. ORCID: https://orcid.org/ 0000-0002-3766-3188
[4]
Institute of Naval Forces, National University “Odessa Maritime
Academy”, 8, Didrikhson Str., Odesa, 65052, Ukraine. Email:
serega.vms@ukr.net. ORCID: https://orcid.org/ 0000-0002-3165-4571
[5]
Department of Technical ship operation of the Institute of Postgraduate
Education, National University “Odessa Maritime Academy”, 8,
Didrikhson Str., Odesa, 65052, Ukraine. Email: oleganaton@gmail.com.
ORCID: https://orcid.org/ 0000-0003-3229-1909
[6]
Department of Logistics, Odessa Military Academy, 10, Fontans'ka Rd, 10, Odesa,
65009 Ukraine. Email: tetiana.ob@ukr.net.
ORCID: https://orcid.org/ 0000-0002-8769-3844