Метод поляризаційної селекції навігаційних об’єктів у складних метеорологічних умовах з використанням статистичних властивостей радіосигналів
This research article is devoted to studying and applying polarization selection for navigation objects in difficult atmospheric conditions. It provides a novel application of Stokes parameters in radar signal processing for navigation objects, validated by experimental data. The main emphasis is on...
Gespeichert in:
| Datum: | 2025 |
|---|---|
| Hauptverfasser: | , , , , , , |
| Format: | Artikel |
| Sprache: | Englisch |
| Veröffentlicht: |
The National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute"
2025
|
| Schlagworte: | |
| Online Zugang: | https://journal.iasa.kpi.ua/article/view/297376 |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| Назва журналу: | System research and information technologies |
| Завантажити файл: |  |
Institution
System research and information technologies| _version_ | 1866302942775083008 |
|---|---|
| author | Korban, Dmytro Melnyk, Oleksiy Kurdiuk, Serhii Onishchenko, Oleg Ocheretna, Valentyna Shcherbina, Olha Kotenko, Oleg |
| author_facet | Korban, Dmytro Melnyk, Oleksiy Kurdiuk, Serhii Onishchenko, Oleg Ocheretna, Valentyna Shcherbina, Olha Kotenko, Oleg |
| author_sort | Korban, Dmytro |
| baseUrl_str | http://journal.iasa.kpi.ua/oai |
| collection | OJS |
| datestamp_date | 2025-05-20T17:56:07Z |
| description | This research article is devoted to studying and applying polarization selection for navigation objects in difficult atmospheric conditions. It provides a novel application of Stokes parameters in radar signal processing for navigation objects, validated by experimental data. The main emphasis is on using the statistical properties of the polarization parameters of partially polarized echo signals. The article discusses in detail the statistical properties of the polarization parameters of partially polarized echo signals, which can be used to improve the accuracy of ship radiolocation systems. The study is based on analyzing experimental data collected in various atmospheric conditions. The results indicate the effectiveness of polarization selection in improving the stability and accuracy of radar navigation systems in various atmospheric conditions. The use of statistical methods allows the navigation system to adapt to changing conditions, ensuring reliability in different scenarios. Polarization selection based on the statistical properties of polarization parameters is a promising method to improve navigation in high atmospheric humidity, fog, and other complex atmospheric conditions. It can be used in the development of modern navigation systems. |
| doi_str_mv | 10.20535/SRIT.2308-8893.2025.1.06 |
| first_indexed | 2025-07-17T10:28:25Z |
| format | Article |
| fulltext |
Publisher IASA at the Igor Sikorsky Kyiv Polytechnic Institute, 2025
Системні дослідження та інформаційні технології, 2025, № 1 73
TIДC
МЕТОДИ АНАЛІЗУ ТА УПРАВЛІННЯ
СИСТЕМАМИ В УМОВАХ РИЗИКУ
І НЕВИЗНАЧЕНОСТІ
UDC 621.396.96
DOI: 10.20535/SRIT.2308-8893.2025.1.06
METHOD OF POLARIZATION SELECTION OF NAVIGATION
OBJECTS IN ADVERSE WEATHER CONDITIONS
USING STATISTICAL PROPERTIES OF RADIO SIGNALS
D. KORBAN, O. MELNYK, S. KURDIUK, O. ONISHCHENKO, V. OCHERETNA,
O. SHCHERBINA, O. KOTENKO
Abstract. This research article is devoted to studying and applying polarization se-
lection for navigation objects in difficult atmospheric conditions. It provides a novel
application of Stokes parameters in radar signal processing for navigation objects,
validated by experimental data. The main emphasis is on using the statistical proper-
ties of the polarization parameters of partially polarized echo signals. The article
discusses in detail the statistical properties of the polarization parameters of partially
polarized echo signals, which can be used to improve the accuracy of ship radioloca-
tion systems. The study is based on analyzing experimental data collected in various
atmospheric conditions. The results indicate the effectiveness of polarization selec-
tion in improving the stability and accuracy of radar navigation systems in various
atmospheric conditions. The use of statistical methods allows the navigation system
to adapt to changing conditions, ensuring reliability in different scenarios. Polariza-
tion selection based on the statistical properties of polarization parameters is a prom-
ising method to improve navigation in high atmospheric humidity, fog, and other
complex atmospheric conditions. It can be used in the development of modern navi-
gation systems.
Keywords: safety of navigation, atmospheric conditions, statistical properties, par-
tially polarized, echo signals, radar systems, navigation equipment, bridge resources,
maritime transport, radiolocation, ship handling and maneuvering.
INTRODUCTION
Over the past decades, high-precision navigation systems have become critical for
a wide range of applications, including autonomous vehicles, unmanned aerial
vehicles, maritime navigation, and others. However, the effectiveness of these
systems can be significantly reduced in difficult atmospheric conditions. The de-
velopment of new methods that ensure stable and efficient navigation in such
conditions is an urgent problem. Thus, the growing need for high-precision radio
navigation systems requires the development of new methods to ensure stable and
efficient navigation in various atmospheric conditions. In this context, polariza-
tion selection of navigation objects seems to be a promising research direction.
Polarization selection is becoming an object of active research to solve these
D. Korban, O. Melnyk, S. Kurdiuk, O. Onishchenko, V. Ocheretna, O. Shcherbina, O. Kotenko
ISSN 1681–6048 System Research & Information Technologies, 2025, № 1 74
problems. This method is based on the use of statistical properties of polarization
parameters of echo signals of partially polarized waves. Light polarization has the
potential to improve signal quality and ensure navigation stability in conditions of
limited visibility and atmospheric instability.
The literature review encompasses a range of topics related to radar systems,
maritime navigation, and signal processing. The discussed works address the is-
sues of ship radar systems, construction of modern high-precision intelligent con-
trol systems for marine vessels [1], navigation support for ship traffic control [2],
analysis of prediction methods for determining the parameters of ship equipment
[3; 4]. In addition, the issues of modeling of radar signals for objects of complex
spatial configuration [5] and scattering of electromagnetic waves by radar objects
[6] are investigated.
The paper [7] contributes insights into the selection of radar signals from
navigation objects in the presence of atmospheric formations. Other works cover
constraints on spatial measurements in phased-array radar due to atmospheric ef-
fects [9], radar detection and identification methods for objects with resonant siz-
es [8], and the influence of propagation medium on maritime direction measure-
ments [10–13], address challenges in measuring the range of low-altitude targets
within the tropospheric waveguide over the sea and the measurement of the Doppler
frequency of signals reflected from targets beyond the radio horizon over the sea.
In [14], a comparison of ship radars operating in different frequency bands
was made. The comprehensive manual on radar, AIS, and target tracking for ma-
rine radar users presented in [15]. The work [16] examined the suitability of
ARPA for the automatic assessment of AIS targets. In [17] discussed ways to en-
hance awareness of maritime situations through the integration of shipborne ra-
dars, [18] explores radars for maritime domain awareness.
In [19; 20] provided essential information on radar technology and the chal-
lenges in the public administration of autonomous shipping, respectively. The
article [21] addresses multi-level challenges in the public administration of navi-
gation safety. Sources [22–30], cover various aspects of maritime safety, vessel
operational efficiency, vulnerability assessment, information security, environ-
mental efficiency, fuzzy controllers in vessel motion control and energy efficient
motion modes contributing significantly to the understanding of modern maritime
operations, safety and technology.
The references [31–43] contribute to the understanding and improvement of
maritime transportation and navigation process safety. These studies cover as-
pects such as public safety management, maritime situational awareness, vessel
equipment vulnerability assessment, vessel information security risks, maritime
transportation security, autonomous vessels, vessel traffic management systems
and energy efficient modes of propulsion systems. They provide valuable insights
into maritime safety issues and developments, offering potential solutions and
improvements for safe navigation [44; 45] in different conditions.
Thus the methodology proposed in this paper provides a comprehensive and
data-driven approach to solving problems related to polarization selection.
Through a thorough literature review, the approach seamlessly integrates statisti-
cal analysis, radar measurements, and practical considerations, offering a sound
basis for effective navigation decision making. Synthesizing these elements not
only improves the understanding of polarization selection methods, but also
makes a valuable contribution to the improvement of shipboard radar systems in
various atmospheric conditions.
Method of polarization selection of navigation objects in adverse weather conditions …
Системні дослідження та інформаційні технології, 2025, № 1 75
MATERIALS AND METHODS
Safe navigation is of paramount importance to ensure the integrated safety of
maritime operations. Ship handling and maneuvering in challenging atmospheric
conditions require accurate and reliable navigation systems. Ship radar, being a
cornerstone of maritime navigation technology, relies on advanced polarization
techniques to accurately detect and analyze echo signals. The utilization of po-
larimetric data in radar systems enhances the precision of object identification,
providing critical information for safe ship handling and maneuvering. By inte-
grating polarimetric insights into radar technology, maritime operators gain a
more comprehensive understanding of their surroundings, enabling proactive
measures for collision avoidance and ensuring a higher level of safety in challeng-
ing atmospheric conditions.
Practical use of polarization parameters of electromagnetic wave in ship-
board radar polarization complexes (SRPC) in solving the problem of polarization
selection of navigation objects located in difficult conditions atmospheric envi-
ronment on the way of the ship, due to the need to use microwave elements and
antenna devices that allow radiation with subsequent analysis of their polarization
parameters. The following antenna devices were used as the SRPC antenna an
omnipolarized antenna with controlled polarization to radiation, which allows to
optimally realize the energy capabilities of SRPC by representing polarization by
real energy Stokes parameters.
During the radar observation of navigation objects against the background of
atmospheric formations, the echo signals arriving at the input of the SRPC re-
ceiver will be reflections from a complex object. Assuming that the Stokes vector
of a complex object has normally distributed components in an arbitrary basis, the
one-dimensional law of distribution of the Stokes parameters of the navigation
object and the atmospheric formation is used to determine the properties of the
echo signal of a complex object received at the SRPC input. The Stokes energy
parameters are quadrature with respect to the field strength of a partially polarized
electromagnetic wave and uniquely determine its polarization. To fully determine
the probability density of the Stokes parameters of the echo signal of a partially
polarized electromagnetic wave scattered by a complex object, it is necessary to
calculate their mean values, variances, and standard deviations.
To address the challenge of polarization selection for navigation objects
amidst atmospheric formations, statistical properties of Stokes parameters of par-
tially polarized electromagnetic waves from the complex object's lunar signals
were utilized. Solving the specified task involves the incorporation of a priori in-
formation characterizing objects of radar observation systems. This a priori in-
formation encompasses the number of observed atmospheric formations (precipi-
tation of varying intensity) that create erroneous markers on the radar indicator.
Additionally, it includes a set of features describing the observed objects, as well
as the probability distribution laws of the feature set.
The set of features that characterize the recognized objects are the energy
polarization parameters of Stokes, which form the predictor, whose components
are the Stokes parameters themselves ),,,( 4321 SSSS . The probabilistic character-
istics of the predictor S are the laws of distribution of the Stokes parameters of
the navigation object and the atmospheric formation.
D. Korban, O. Melnyk, S. Kurdiuk, O. Onishchenko, V. Ocheretna, O. Shcherbina, O. Kotenko
ISSN 1681–6048 System Research & Information Technologies, 2025, № 1 76
The echo signals of a navigation object are equivalent to the presence of a
polarized component in the echo signal of the total partially polarized wave of a
complex object. The fluctuating component of the echo signal of the total partially
polarized wave of a complex object caused by reflection from an atmospheric
formation corresponds in its statistical properties to the echo signal of a partially
polarized wave subject to the central limit theorem of probability theory. In the
case of a navigation object in the area of an atmospheric formation (Figure), the
reflection of an electromagnetic wave irradiating two objects (a complex object)
with different electrical conductivity (metal and water in liquid or solid state) at
the same time is equivalent to the presence of a polarized component (navigation
object) and a fluctuating component (atmospheric formation).
When receiving an echo signal of a partially polarized electromagnetic wave
simultaneously from two objects (a complex object), all four Stokes parameters
are recorded simultaneously, and their criterion values are set based on the values.
At the same time, for a navigation object, polarization selection of its echo signals
is performed against the background of echo signals from an atmospheric formation.
To solve the problem of polarization selection of echo signals of a naviga-
tion object, the laws of distribution of predictors are used )/( HOSW navigation
object and )/( AUSW of the atmospheric formation, which in the theory of rec-
ognition are functions of the probability of the feature vectors of predictors S ,
which will include the Stokes parameters of the navigation object and the atmos-
pheric formation. These laws show the probability of forming predictors S з
with given values of the Stokes parameters, provided that the echo signals are
generated by the navigation object and the atmospheric formation, and the distri-
bution of the reflectivity of the predictors S can be described by normal laws.
Since these predictor S distribution laws intersect, the problem of polarization
selection of the navigation object is solved using the maximum likelihood rule,
which is defined by the following inequality:
1
)/(
)/(
АOSW
HOSW
п
п . (1)
Radar observation of a navigation object against the background of an atmospheric formation
Relative position
R
el
at
iv
e
po
si
ti
on
Method of polarization selection of navigation objects in adverse weather conditions …
Системні дослідження та інформаційні технології, 2025, № 1 77
Expression (1) for the four Stokes parameters of the echo signal of a partially
polarized wave is written as follows:
1
)/(
)/(
1
1
АOSW
HOSW
, 1
)/(
)/(
2
2
АOSW
HOSW
, 1
)/(
)/(
3
3
АOSW
HOSW
, 1
)/(
)/(
4
4
АOSW
HOSW
. (2)
Since the reflectivity distribution of the Stokes parameters can be described
by normal laws, then inequalities (2) are given in the form:
;
2
1
2
1
)/(
)/(
;
2
1
2
1
)/(
)/(
2
2
2
2
2
2
2
2
1
2
2
1
2
)(
2
)(
2
2
2
)(
2
)(
1
1
AO
AO
HO
HO
AO
AO
HO
HO
mS
AU
mS
НО
mS
AU
mS
НО
е
е
АUSW
HOSW
е
е
АUSW
HOSW
;
2
1
2
1
)/(
)/(
2
2
3
2
2
3
2
)(
2
)(
3
3
AO
AO
HO
HO
mS
AU
mS
НО
е
е
АUSW
HOSW
,
2
1
2
1
)/(
)/(
2
2
4
2
2
4
2
)(
2
)(
4
4
AO
AO
HO
HO
mS
AU
mS
НО
е
е
АUSW
HOSW
(3)
where 4321 ,,, SSSS — measured Stokes parameters of a complex SRPC observa-
tion object; АUНО , — statistical parameter — the standard deviation for the
general population of a series of observations of the Stokes parameters of the nav-
igation object and the atmospheric formation, respectively; АUНО тт , — statisti-
cal parameter — mathematical expectations of the Stokes parameters of the echo
signals of the navigation object and the atmospheric formation, respectively;
22 , АUНО — statistical parameter — the variances of the Stokes parameters of the
echo signals of the navigation object and the atmospheric formation, respectively.
Transforming the right-hand side of equations (3) according to the
expression for the exponential function
b
a
baba
e
e
eee allows us to obtain
the following dependencies for the right-hand side of the distribution laws of the
predictor of the navigation object and the atmospheric formation.
To provide a comprehensive understanding of the underlying physics, we
include the mathematical model that relates the Stokes parameters of the electro-
magnetic wave to the radar object's properties. The Stokes parameters
),,,( 4321 SSSS describe the polarization state of an electromagnetic wave and are
D. Korban, O. Melnyk, S. Kurdiuk, O. Onishchenko, V. Ocheretna, O. Shcherbina, O. Kotenko
ISSN 1681–6048 System Research & Information Technologies, 2025, № 1 78
derived from the electric field components. The reflected signals can be repre-
sented as the result of the interaction of the electromagnetic wave with the target,
possessing certain radar characteristics. The Stokes parameters can be expressed
through the target characteristics as follows:
Total power of the wave 1S related to the reflection coefficient R of the target:
RES i
2
1 ,
where 2
iE is the amplitude of the incident wave.
Horizontal and vertical polarizations are related to the scattering components
hR and vR :
)(2
2 vhi RRES .
Polarization at 45° and –45°:
)( 4545
2
2 RRES i ,
where 45R and RR 45 are the scattering components at 45° and –45° respectively
Right-hand and left-hand circular polarizations:
)(2
3 lcprcpi RRES ,
where rcpR and lcpR are the scattering components of right-hand and left-hand
circular polarization respectively.
Considering the statistical properties of the Stokes parameters, the maximum
likelihood method can be applied to determine the target parameters. The prob-
ability of the measured values of the Stokes parameters iS for a target and atmos-
pheric conditions can be written as:
2
2
2 σ2
)μ(
exp
πσ2
1
)θ( i
i
S
SP ,
where represents the target parameters, and and are the mean and stan-
dard deviation of the Stokes parameters respectively.
The Stokes parameters ),,,( 4321 SSSS are derived from the received radar
signals by first decomposing the signals into their horizontal )( HE and vertical
)( VE components using polarimetric radar techniques. The Stokes parameters are
then calculated using the following relations of magnitudes of the horizontal and
vertical components of the electric field, respectively and the complex conjugate
product of these components, which captures the cross-polarization information.
The derived Stokes parameters are then used in the statistical decision-
making process to determine the presence of a radar target. This involves
applying the maximum likelihood rule and evaluating the probability densities of
the Stokes parameters for both the navigation object and the atmospheric
formations. By following these steps, the radar system can effectively
differentiate between the echo signals of navigation objects and atmospheric
formations, enhancing the accuracy and reliability of radar-based navigation in
challenging conditions.
These parameters are subsequently used in the statistical decision-making
process, applying the maximum likelihood rule to evaluate the probability
densities and determine the presence of a radar target amidst atmospheric formations.
Method of polarization selection of navigation objects in adverse weather conditions …
Системні дослідження та інформаційні технології, 2025, № 1 79
Let us transform the right-hand side of the equation for the first Stokes pa-
rameter and obtain:
2
2
1
2
2
1
2
2
1
2
2
1
2
)(
2
)(
2
)(
2
)(
2
1
2
1
AU
AU
HO
HO
AU
AU
HO
HO
mS
НО
mS
AU
mS
AU
mS
НО
е
е
е
е
1
22
2222
122
22
2
122
22
2
)()(
2
)(
АUНО
HOАUAUНО
АUНО
AUHОHOAU
АUНО
АUНО
mm
S
mm
S
НО
AU е ; (4)
Similar results are obtained for the second, third, and fourth Stokes parameters:
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
1
2
1
AU
AU
HO
HO
AU
AU
HO
HO
mS
НО
mS
AU
mS
AU
mS
НО
е
е
е
е
1
22
2222
122
22
2
122
22
2
)()(
2
)(
АUНО
HOАUAUНО
АUНО
AUHОHOAU
АUНО
АUНО
mm
S
mm
S
НО
AU е ; (5)
2
2
3
2
2
3
2
2
3
2
2
3
2
)(
2
)(
2
)(
2
)(
2
1
2
1
AU
AU
HO
HO
AU
AU
HO
HO
mS
НО
mS
AУ
mS
AU
mS
НО
е
е
е
е
1
22
2222
122
22
2
122
22
2
)()(
2
)(
АUНО
HOАUAUНО
АUНО
AUHОHOAU
АUНО
АUНО
mm
S
mm
S
НО
AU е ; (6)
2
2
4
2
2
4
2
2
4
2
2
4
2
)(
2
)(
2
)(
2
)(
2
1
2
1
AU
AU
HO
HO
AU
AU
HO
HO
mS
НО
mS
AU
mS
AU
mS
НО
е
е
е
е
D. Korban, O. Melnyk, S. Kurdiuk, O. Onishchenko, V. Ocheretna, O. Shcherbina, O. Kotenko
ISSN 1681–6048 System Research & Information Technologies, 2025, № 1 80
1
22
2222
122
22
2
122
22
2
)()(
2
)(
АUНО
HOАUAUНО
АUНО
AUHОHOAU
АUНО
АUНО
mm
S
mm
S
НО
AU е . (7)
Let us denote the statistical parameters of degree e in equations (4)–(7) by
the coefficients 321 ,, lll i.e:
;
2
)(
22
22
1
АUНО
АUНОl
;
)(
22
22
2
АUНО
AUHОHOAU mm
l
22
2222
3
2
)(
АUНО
НОАUАUНО mm
l
, (8)
then inequalities (4)–(7) will be written in terms of the coefficients 321 ,, lll as
follows:
1312
2
11
lSlSl
НО
AU е ; (9)
1322
2
21
lSlSl
НО
AU е ; (10)
1332
2
31
lSlSl
НО
AU е ; (11)
1342
2
41
lSlSl
НО
AU е . (12)
After logarithmizing on the basis of e, inequalities (9)–(12) are written as
follows:
AU
HОlnlSlSl
312
2
11 ; (13)
AU
HОlnlSlSl
322
2
21 ; (14)
AU
HОlnlSlSl
312
2
11 ; (15)
AU
HОlnlSlSl
342
2
41 . (16)
Solution of the obtained inequalities (13)–(16) with respect to the Stokes pa-
rameters 4321 ,,, SSSS of echo signals of a partially polarized wave of a complex
object allows to obtain their criterion values krkrkrkr SSSS 4321 ,,, . Then, for all the
Stokes parameters measured by SRPC msrmsrmsrmsr SSSS 4321 ,,, their values will
be greater than or equal to their criterion values, i.e.:
krmsrkrmsrkrmsrkrmsr SSSSSSSS 44332211 ,,,
and inequalities (13)–(16) will be valid. The operator of the SRPC shall decide on
the presence on the indicator or display of the ship's computer of the echo signal
only of the navigation object located at a given distance from the SRPC.
Method of polarization selection of navigation objects in adverse weather conditions …
Системні дослідження та інформаційні технології, 2025, № 1 81
If the conditions of the above inequalities are not met, a decision is made on
the presence of an atmospheric formation on the indicator of the SRPC or the dis-
play of the ship's computer, i.e.
1msrS < 1krS , 2msrS < krS2 , 3msrS < 3krS , 4msrS < 4krS .
The basis for the use of the basic concepts of mathematical statistics and
probability theory is the randomness of echo signals of Stokes parameters in the
process of radar observation of navigation objects located in the zone of
atmospheric formations by SRPC. The use of the maximum likelihood algorithm
in solving the problem of polarization selection of navigation objects makes it
possible to assign an echo signal to the object for which the likelihood function is
greater.
The polarization selection of navigation objects using the maximum
likelihood rule uses a smaller amount of a priori radar information and therefore
the application of this rule is practically justified. When studying the values of the
Stokes parameters of echo-signals for a navigation object and an atmospheric
formation, their probability density distributions are close to normal, and the set
of random values of the Stokes parameters of echo-signals of a navigation object
and an atmospheric formation is considered as a random process of a complex
object.
The values of the Stokes parameters of the navigation object and the
atmospheric formation at discrete points in space and time were obtained for a
certain period of time based on the results of radar measurements of the SRPC in
the Zaporizhzhia region (Ukraine), taking into account the intensity of random
precipitation and taking into account the radar information obtained in parallel
with the MRL-5 meteorological radar. According to the obtained radar
measurements of the SRPC, the echo signals of the first Stokes parameter of the
navigation object and the atmospheric formation for a certain intensity of
precipitation (in this case 12I mm/hour), statistical processing of the results of
measuring the first Stokes parameter HOS1 and AUS1 , which are presented in
Table 1 and Table 2, respectively.
T a b l e 1 . Results of radar observations of the SRPC echo-signal of a naviga-
tion object located in the zone of atmospheric formation and parameters of their
statistical processing
Grades S1НО f NfP / Sс d fd d2 fd2
0.00 – 0.49 4 0.040 0.245 - 0.40 - 1.60 0.16 0.64
0.50 – 0.99 9 0.091 0.745 - 0.30 - 2.70 0.09 0.81
1.00 – 1.49 10 0.101 1.245 - 0.20 - 2.00 0.04 0.40
1.50 – 1.99 15 0.152 1.745 - 0.10 - 1.50 0.01 0.15
2.00 – 2.49 21 0.212 2.245 0.00 0.00 0.00 0.00
2.50 – 2.99 13 0.131 2.745 0.10 1.30 0.01 0.13
3.00 – 4.49 10 0.101 3.245 0.20 2.00 0.04 0.40
3.50 – 3.99 9 0.091 3.745 0.30 2.70 0.09 0.81
4.00 – 4.49 5 0.051 4.245 0.40 2.00 0.16 0.80
4.50 – 4.99 3 0.030 4.745 0.50 1.50 0.25 0.75
∑ f=N 99 1.000 ∑ 1.70 ∑ 4.90
D. Korban, O. Melnyk, S. Kurdiuk, O. Onishchenko, V. Ocheretna, O. Shcherbina, O. Kotenko
ISSN 1681–6048 System Research & Information Technologies, 2025, № 1 82
T a b l e 2 . Results of radar observations of the SRPC echo-signal of atmos-
pheric formation and parameters of their statistical processing
Grades S1АU f NfP / 1S d fd d2 fd2
0.00 – 0.49 3 0.033 0.245 - 0.30 - 0.90 0.09 0.27
0.50 – 0.99 2 0.022 0.745 - 0.20 - 0.40 0.04 0.08
1.00 – 1.49 19 0.209 1.245 - 0.10 - 1.90 0.01 0.19
1.50 – 1.99 35 0.385 1.745 0.00 0.00 0.00 0.00
2.00 – 2.49 20 0.220 2.245 0.10 2.00 0.01 0.20
2.50 – 2.99 6 0.066 2.745 0.20 1.20 0.04 0.24
3.00 – 4.49 4 0.044 3.245 0.30 1.20 0.09 0.36
3.50 – 3.99 2 0.023 3.745 0.40 0.80 0.16 0.32
∑ f=N 91 1.000 ∑ 2.00 ∑ 1.66
Statistical processing of the results of radar observations of the navigation
object and the atmospheric formation was carried out using statistical methods. In
Tables 1 and 2, for each gradation of Stokes parameters HOS1 и AUS1 indicates
the frequency f (number of cases). Sum of frequencies f of all grades of
Stokes parameters is equal to the total number of observations N. Relationship
NfP / is the probability of occurrence of a given gradation. The average value
1S for each gradation is calculated using the following formula:
N
fd
iAS
1 , (17)
where А — the middle of the gradation with the largest amount of data 1S , that is,
for a navigation object 245.2A , and for atmospheric formation 745.1A ; i —
the size of the gradation (for our case 5i );
i
AS
d с — a positive or negative
number indicating the number of the gradation.
The mathematical expectation for a navigation object and an atmospheric
formation is determined using the following relationship:
N
fd
iAmS
АUiННSАUНО
)()(1 . (18)
The mean square deviation determines the degree of variability of the ran-
dom first Stokes parameter for the navigation object and the atmospheric forma-
tion, which is determined by the formula:
i
22
N
fd
N
fd
. (19)
The variance, as the square of the standard deviation, is determined by the
following formula:
1
22
N
N
. (20)
Based on the results of Tables 1 and 2 and the above formulas, we calculated
the relevant statistical characteristics, i.e.:
Method of polarization selection of navigation objects in adverse weather conditions …
Системні дослідження та інформаційні технології, 2025, № 1 83
1.3
1
HOSm ; 1.1
1
HOS ; 21.12
1
HOS
.
85.1
1
АUSm ; 66.0
1
АUS ; 44.02
1
АUS
.
Using the statistical parameters of the echo signals of the navigation object
and the atmospheric formation, we calculated the coefficients 321 ,, lll , which
have the following values: 44.0,88.0,72.0 321 lll . After substituting
them into inequality (9), we obtain:
055.088.072.0 1
2
1 SS . (21)
Solving inequality (21), we obtain two criterion values of the first Stokes pa-
rameter 68.1)1(1 krS and 46.0)2(1 krS . Criterion value of the first Stokes pa-
rameter 46.0)2(1 krS is rejected for physical reasons, since the probability of its
occurrence for radar detection of the SRPC navigation object is zero, according to
radar observations of a complex object. Therefore, the value of the first Stokes
parameter 68.1)1(1 krS will satisfy the solution of the problem of polarization
selection of a navigation object located in the zone of atmospheric formation
(precipitation of a certain intensity) and, when radar measurements of the echo
signals of the first Stokes parameter are performed, will meet the following condi-
tions 68.1)1(1 krS . That is, the task of polarization selection of the navigation
object is solved. which is located in the zone of atmospheric formation (precipita-
tion intensity of 12 mm/h). In this case, only the echo signal of the navigation
object will be present on the SRPC indicator or on the computer display.
The polarization selection of navigation objects using the maximum likeli-
hood rule (1) uses a smaller amount of a priori radar information and therefore the
application of this rule is practically justified. To verify the fulfillment of condi-
tion (1), we solve equation (3) using the obtained statistical parameters.
For a navigation object: 1.3
1
HOSm ; 1.1
1
HOS ; 21.12
1
HOS
4; 2.21 HOS .
95.06.236.0
1.15.2
1
2
1
)/( 2.12
)1.32.2(
2
)(
1
2
2
2
1
ееHOSW
HO
HOmS
НО
.
For atmospheric formation: 85.1
1
АUSm ; 66.0
1
АUS ; 44.02
1
АUS
;
75.11 AUS .
67.01.161.0
66.05.2
1
2
1
)/( 44.02
)85.175.1(
2
)(
1
2
2
2
1
ееАUSW
АU
АUmS
АU
.
4.1
67.0
95.0
)/(
)/(
1
1
АUSW
HOSW
.
As a result of solving equation (3) using the first Stokes parameter as a pre-
dictor, the maximum likelihood rule (1) is fulfilled.
D. Korban, O. Melnyk, S. Kurdiuk, O. Onishchenko, V. Ocheretna, O. Shcherbina, O. Kotenko
ISSN 1681–6048 System Research & Information Technologies, 2025, № 1 84
Thus the method proposed for polarized selection of navigation objects in
challenging atmospheric conditions through shipboard radar polarization com-
plexes (SRPC) involves a sophisticated approach. Leveraging the statistical prop-
erties of Stokes parameters from partially polarized electromagnetic waves de-
rived from lunar signals of complex objects, the technique integrates a priori
information to enhance radar observation system capabilities.
A pivotal aspect is the utilization of an omnipolarized antenna with con-
trolled polarization, emphasizing the optimization of SRPC's energy capabilities
by representing polarization through real energy Stokes parameters. The analysis
of echo signals involves the simultaneous recording of all four Stokes parameters,
enabling the polarization selection of navigation objects amidst atmospheric for-
mations.
The application of the maximum likelihood rule is highlighted as a key com-
ponent, demonstrating its practical justification due to its efficiency, particularly
when a limited amount of a priori radar information is available. The derivation of
criterion values for Stokes parameters is integral to the process, contributing to
informed decision-making.
Radar measurements, considering precipitation intensity and utilizing data
from a meteorological radar, provide a real-world context for the study. The sta-
tistical processing of radar observations for navigation objects and atmospheric
formations involves the calculation of coefficients and verification of statistical
parameters.
Accurate identification and tracking of navigation objects even in challeng-
ing atmospheric conditions provides ship operators with critical information to
make informed decisions during maneuvers. This not only helps avoid collisions,
but also enhances the safety of maritime activities. The integration of advanced
polarimetric techniques is in line with the broader goal of improving navigation
safety in a variety of environmental conditions.
CONCLUSIONS
The presented study outlines a systematic and data-driven methodology for po-
larimetric extraction of navigational objects in complex atmospheric conditions
using shipboard radar polarization systems (SRPC). Using statistical properties of
the Stokes parameters of partially polarized electromagnetic waves derived from
lunar signals of complex objects, this approach integrates a priori information to
improve the performance of radar surveillance systems.
The use of an omnipolarized antenna with controlled polarization is a critical
element that emphasizes the optimization of SRPC energy capabilities by repre-
senting polarization through real Stokes energy parameters. The analysis of the
echo signals includes simultaneous registration of all four Stokes parameters, en-
abling polarization selection of navigation objects in complex atmospheric forma-
tions.
The key point is the application of the maximum likelihood rule, which
demonstrates its practical justification due to its effectiveness, especially in the
conditions of limited amount of a priori radar information. The derivation of crite-
rion values for the Stokes parameters is an integral part of the process, allowing
informed decisions to be made in the context of polarization selection. The meth-
Method of polarization selection of navigation objects in adverse weather conditions …
Системні дослідження та інформаційні технології, 2025, № 1 85
odology offers a comprehensive and rigorous approach to polarization selection
problems, demonstrating the integration of statistical analysis, radar measure-
ments, and practical considerations. The results contribute to the understanding of
polarimetric selection methods in navigation systems and may find applications in
improving the performance of ship radar systems in various atmospheric conditions.
REFERENCES
1. A.P. Ben, I.V. Palamarchuk, “Features of the construction of modern high-precision
intelligent control systems for the movement of sea vessels,” Scientific Bulletin of
the Kherson State Maritime Academy, 1(14), pp. 4–10, 2016.
2. V.I. Bogomya, V.S. Davidov, V.V. Doronin, D.P. Pashkov, and I.V. Tikhonov, Nav-
igation support for vessel traffic management. Kyiv: DVVP “Kompas”, 2012.
3. A.A. Musorin, Y.E. Shapran, and I.V. Trofimenko, “Analysis of forecasting methods
for determining the technical parameters of ship equipment,” Proceedings of Azerbaijan
State Marine Academy, 2, pp. 115–119, 2017.
4. O.O. Musorin, Y.E. Shapran, and I.V. Trofimenko, “Features of analytical support
for vessel operation in modern conditions,” Scientific Notes of the Ukrainian
Research Institute of Communications, 1(45), pp. 117–121, 2017.
5. V.V. Mal'tsev, I.V. Sisigin, and K.O. Kolesnikov, “Approach to modeling radar sig-
nals reflected from objects of complex spatial configuration,” Radiopromyshlennost,
1, pp. 42–49, 2018.
6. S.V. Nechitaylo, V.M. Orlenko, O.I. Sukharevsky, and V.A. Vasilets, Electromag-
netic Wave Scattering by Aerial and Ground Radar Objects. Boca Raton, USA: SRC
Press Taylor & Francis Group, 2014, 334 p.
7. D.V. Korban, “Selection of radar signals from navigation objects located in the zone
of atmospheric formations,” in Proceedings of the Scientific and Technical Confer-
ence “Marine and River Fleet: Operation and Repair,” March 24–25, 2022, Odessa:
NU “OMA”, pp. 25–28.
8. G.S. Zalevsky, A.V. Muzychenko, and O.I. Sukharevsky, “Method of Radar Detec-
tion and Identification of Metal and Dielectric Objects with Resonant Sizes Located
in Dielectric Medium,” Radioelectronics and Communications Systems, vol. 55,
no. 9, pp. 393–404, 2012.
9. O.L. Kuznetsov, O.B. Tantsyura, and O.L. Melnyk, “Constraints on the quality of
spatial measurements in phased-array radar due to the influence of atmospheric in-
homogeneities and the Earth’s surface,” Systems of Navigation and Communication,
1 (21), vol. 2, pp. 49–52, 2012.
10. V.D. Karlov, N.N. Petrushenko, V.V. Chelpanov, and K.P. Kvitkin, “The influence
of the propagation medium on the maritime direction when measuring the angular
coordinates of radar targets,” Collection of scientific works of the Kharkiv University
of the Air Force, 3 (25), pp. 51–53, 2010.
11. V.D. Karlov, D.B. Kucher, O.V. Strutsynsky, and O.V. Lukashuk, “On the issue of
measuring the range of a low-altitude target during its radar tracking within the tro-
pospheric waveguide over the sea,” Science and Technology of the Air Force of the
Armed Forces of Ukraine, 3 (24), pp. 98–101, 2016.
12. V.D. Karlov, A.P. Kondratenko, A.K. Sheigas, and Y.B. Sitnik, “On the issue of
measuring the Doppler frequency of a signal reflected from a target located beyond
the radio horizon over the sea,” Science and Technology of the Air Force of the
Armed Forces of Ukraine, 1(14), pp. 115–117, 2014.
13. V.D. Karlov, A.O. Rodyukov, and I.M. Pichugin, “Statistical characteristics of radar
signals reflected from local objects under conditions of anomalous refraction,”
Science and Technology of the Air Force of the Armed Forces of Ukraine, 4(21),
pp. 71–74, 2015.
D. Korban, O. Melnyk, S. Kurdiuk, O. Onishchenko, V. Ocheretna, O. Shcherbina, O. Kotenko
ISSN 1681–6048 System Research & Information Technologies, 2025, № 1 86
14. A.P. Gorobtsov, A.N. Marinich, and Y.M. Ustinov, “Comparison of ship radars op-
erating in S-, X-, K-bands,” Bulletin of the State University of the Maritime and Riv-
er Fleet named after Admiral S.O. Makarov, 5(51), pp. 1087–1093, 2018. doi:
https://doi.org/10.21821/2309-5180-2018-10-5-1087-1093
15. A.G. Bole, A.D. Wall, and A. Norris, Radar and ARPA Manual: Radar, AIS and
Target Tracking for Marine Radar Users (3rd edition). Oxford, United Kingdom:
Elsevier Science & Technology, 2014.
16. F. Heymann, T. Noack, P. Banyś, and E. Engler, “Is ARPA Suitable for Automatic
Assessment of AIS Targets?,” Marine Navigation and Safety of Sea Transportation,
pp. 223–232, 2013. doi: https://doi.org/10.1201/b14961-40
17. V.I. Konoverts, N.B. Smyrinska, “Ways to enhance awareness of the maritime situa-
tion through the integration of shipborne radars into the surface situation display sys-
tem,” Collection of Scientific Works of Kharkiv National University of the Air Force,
4(66), pp. 71–78, 2020. doi: https://doi.org/10.30748/zhups.2020.66.10
18. A.M. Ponsford, “Radars for Maritime Domain Awareness,” Conference “Military
Radar Summit,” Arlington (VA), Virginia, 2015. doi: http://dx.doi.org/10.13140/
RG.2.1.3961.7687
19. A. Bole, A. Wall, and A. Norris, Radar and ARPA Manual; 3rd ed. Oxford, UK:
Elsevier Butterworth-Heineman, 2014.
20. D. Luchenko, І. Georgiievskyi, and M. Bielikova, “Challenges and Developments in
the Public Administration of Autonomous Shipping,” Lex Portus, 9 (1), pp. 20–36,
2023. doi: 10.26886/2524-101X.9.1.2023.2
21. T. Plachkova, O. Avdieiev, “Public administration of safety of navigation: Multi-
level challenges and answers,” Lex Portus, 5 (25), pp. 34–62, 2020. doi:
10.26886/2524-101X.5.2020.2
22. O. Melnyk, Y. Bychkovsky, and A. Voloshyn, “Maritime situational awareness аs a
key measure for safe ship operation,” Scientific Journal of Silesian University of
Technology. Series Transport, 114, pp. 91–101, 2022. doi: https://doi.org/10.20858/
sjsutst.2022.114.8
23. O. Melnyk, M. Malaksiano, “Effectiveness assessment of non-specialized vessel ac-
quisition and operation projects, considering their suitability for oversized cargo
transportation,” Transactions on Maritime Science, 9 (1), pp. 23–34, 2020. doi:
10.7225/toms.v09.n01.00223
24. O. Melnyk et al., “Autonomous Ships Concept and Mathematical Models Applica-
tion in their Steering Process Control,” TransNav, 16 (3), pp. 553–559, 2022. doi:
10.12716/1001.16.03.18
25. O. Melnyk, S. Onyshchenko, “Navigational safety assessment based on Markov-
model approach,” Scientific Journal of Maritime Research, 36 (2), pp. 328–337,
2022. doi: https://doi.org/10.31217/p.36.2.16
26. O. Melnyk, S. Onyshchenko, O. Onishchenko, O. Lohinov, and V. Ocheretna, Inte-
gral approach to vulnerability assessment of ship’s critical equipment and systems,
Transactions on Maritime Science, vol. 12, no. 1, 2023. doi: https://doi.org/10.7225/
toms.v12.n01.002
27. O. Melnyk et al., “Review of Ship Information Security Risks and Safety of
Maritime Transportation Issues,” TransNav, 16 (4), pp. 717–722, 2022. doi:
10.12716/1001.16.04.13
28. O. Melnyk et al., “Study of Environmental Efficiency of Ship Operation in Terms of
Freight Transportation Effectiveness Provision,” TransNav, vol. 16, no. 4, pp. 723–722,
2022. doi: 10.12716/1001.16.04.14
29. O. Melnyk et al., “Application of Fuzzy Controllers in Automatic Ship Motion Con-
trol Systems,” International Journal of Electrical and Computer Engineering,
vol. 13, no.4, pp. 3948–3957, 2023. doi: 10.11591/ijece.v13i4.pp3948-3957
Method of polarization selection of navigation objects in adverse weather conditions …
Системні дослідження та інформаційні технології, 2025, № 1 87
30. Y. Volyanskaya, S. Volyanskiy, A. Volkov, and O. Onishchenko, “Determining en-
ergy-efficient operation modes of the propulsion electrical motor of an autonomous
swimming apparatus,” Eastern-European Journal of Enterprise Technologies, 6
(8-90), pp. 11–16, 2017. doi: 10.15587/1729-4061.2017.118984
31. V.A. Golikov, V.V. Golikov, Y. Volyanskaya, O. Mazur, and O. Onishchenko,
“A simple technique for identifying vessel model parameters,” IOP Conference
Series: Earth and Environmental Science, 172 (1), art. no. 012010, 2018. doi:
10.1088/1755-1315/172/1/012010
32. V. Budashko, V. Nikolskyi, O. Onishchenko, and S. Khniunin, “Decision support
system's concept for design of combined propulsion complexes,” Eastern-European
Journal of Enterprise Technologies, 3 (8-81), pp. 10–21, 2016. doi: 10.15587/1729-
4061.2016.72543
33. V. Budashko, T. Obniavko, O. Onishchenko, Y. Dovidenko, and D. Ungarov, “Main
Problems of Creating Energy-efficient Positioning Systems for Multipurpose Sea
Vessels,” 2020 IEEE 6th International Conference on Methods and Systems of Naviga-
tion and Motion Control, MSNMC 2020 - Proceedings, art. no. 9255514, pp. 106–109.
doi: 10.1109/MSNMC50359.2020.9255514
34. G.K. Lavrenchenko, A.G. Slinko, A.S. Boychuk, S.V. Kozlovskyi, and V.M. Halkin,
“Conversion of liquid to steam. How and why?,” Journal of Chemistry and Tech-
nologies, 31 (3), pp. 678–684, 2023. doi: 10.15421/jchemtech.v31i3.285771
35. L.A. Frolova, T.V. Hrydnieva, “Influence of various factors on the ferric α-
oxyhydroxide synthesis,” Journal of Chemistry and Technologies, 28 (1), pp. 61–67,
2020. doi: 10.15421/082008
36. A. Bondar, N. Bushuyeva, S.D. Bushuyev, and S. Onyshchenko, “Modelling of Cre-
ation Organisational Energy-Entropy,” International Scientific and Technical Con-
ference on Computer Sciences and Information Technologies, 2, art. no. 9321997,
pp. 141–145, 2020. doi: 10.1109/CSIT49958.2020.9321997
37. S. Onyshchenko, A. Bondar, V. Andrievska, N. Sudnyk, and O. Lohinov, “Con-
structing and exploring the model to form the road map of enterprise development,”
Eastern-European Journal of Enterprise Technologies, 5 (3-101), pp. 33–42, 2019.
10.15587/1729-4061.2019.179185
38. S. Bushuyev, V. Bushuieva, S. Onyshchenko, and A. Bondar, “Modeling the dynam-
ics of information panic in society. COVID-19 case,” CEUR Workshop Proceedings,
2864, pp. 400–408, 2021.
39. A. Bondar, S. Onyshchenko, O. Vishnevska, D. Vishnevskyi, S. Glovatska, and A.
Zelenskyi, “Constructing and investigating a model of the energy entropy dynamics
of organizations,” Eastern-European Journal of Enterprise Technologies, 3 (3-105),
pp. 50–56, 2020. doi: 10.15587/1729-4061.2020.206254
40. O. Scherbina, O. Drozhzhyn, O. Yatsenko, and O. Shybaev, “Cooperation forms be-
tween participants of the inland waterways cargo delivery: a case study of the Dnie-
per region,” Scientific Journal of Silesian University of Technology. Series Trans-
port, 103, pp. 155–166, 2019. doi: 10.20858/sjsutst.2019.103.12
41. A. Shibaev, S. Borovyk, and I. Mykhailova, “Developing a strategy for modernizing
passenger ships by the optimal distribution of funds,” Eastern-European Journal of
Enterprise Technologies, 6 (3-108), pp. 33–41, 2020. doi: 10.15587/1729-
4061.2020.219293
42. D.S. Minchev et al., “Prediction of centrifugal compressor instabilities for internal
combustion engines operating cycle simulation,” Proceedings of the Institution of
Mechanical Engineers, Part D: Journal of Automobile Engineering, 237 (2-3),
pp. 572–584, 2023. doi: 10.1177/09544070221075419
43. R. Varbanets et al., “Concept of Vibroacoustic Diagnostics of the Fuel Injection and
Electronic Cylinder Lubrication Systems of Marine Diesel Engines,” Polish Mari-
time Research, 29 (4), pp. 88–96, 2022. doi: 10.2478/pomr-2022-0046
D. Korban, O. Melnyk, S. Kurdiuk, O. Onishchenko, V. Ocheretna, O. Shcherbina, O. Kotenko
ISSN 1681–6048 System Research & Information Technologies, 2025, № 1 88
44. M. Stetsenko et al., “Improving Navigation Safety by Utilizing Statistical Method of
Target Detection on the Background of Atmospheric Precipitation,” Trends in Sus-
tainable Computing and Machine Intelligence - Proceedings of ICTSM 2023. doi:
https://doi.org/10.1007/978-981-99-9436-6_8
45. D. Korban, O. Melnyk, O. Onishchenko, S. Kurdiuk, V. Shevchenko, and T. Ob-
niavko, “Radar-based detection and recognition methodology of autonomous surface
vehicles in challenging marine environment,” Scientific Journal of Silesian University of
Technology. Series Transport, 122, pp. 111–127, 2024. doi: 10.20858/sjsutst.2024.122.7
Received 30.01.2024
INFORMATION ON THE ARTICLE
Dmytro V. Korban, ORCID: 0000-0002-6798-2526 , National University “Odesa
Maritime Academy”, Ukraine, e-mail: korbandmv@gmail.com
Oleksiy M. Melnyk, ORCID: 0000-0001-9228-8459, Odesa National Maritime
University, Ukraine, e-mail: m.onmu@ukr.net
Serhii V. Kurdiuk, ORCID: 0000-0002-3165-4571, National University “Odesa Mari-
time Academy”, Ukraine, e-mail: serega15507@ukr.net
Oleg A. Onishchenko, ORCID: 0000-0002-3766-3188, National University “Odesa
Maritime Academy”, Ukraine, e-mail: oleganaton@gmail.com
Valentyna V. Ocheretna, ORCID: 0000-0003-4077-6711, Odesa National Maritime
University, Ukraine, e-mail: v.ocheretna@ukr.net
Olha V. Shcherbina, ORCID: 0000-0002-9247-5972, Odesa National Maritime Univer-
sity, Ukraine, e-mail: olshcherbina@i.ua
Oleg V. Kotenko, ORCID: 0009-0007-5294-474X, Odesa National Maritime University,
Ukraine, e-mail: kot_ov@ukr.net
МЕТОД ПОЛЯРИЗАЦІЙНОЇ СЕЛЕКЦІЇ НАВІГАЦІЙНИХ ОБ’ЄКТІВ
У СКЛАДНИХ МЕТЕОРОЛОГІЧНИХ УМОВАХ З ВИКОРИСТАННЯМ
СТАТИСТИЧНИХ ВЛАСТИВОСТЕЙ РАДІОСИГНАЛІВ / Д.В. Корбан,
О.М. Мельник, С.В. Курдюк, О.А. Онищенко, В.В. Очеретна, О.В. Щербина, О.В. Котенко
Анотація. Присвячено дослідженню та застосуванню поляризаційної селекції
для навігаційних об’єктів у складних атмосферних умовах. Основний акцент
зроблено на використанні статистичних властивостей поляризаційних параме-
трів частково поляризованих ехо-сигналів. Детально розглянуто статистичні
властивості поляризаційних параметрів частково поляризованих ехо-сигналів,
які можуть бути використані для підвищення точності суднових радіолокацій-
них систем. Дослідження ґрунтується на аналізі експериментальних даних, зі-
браних у різних атмосферних умовах. Отримані результати свідчать про ефек-
тивність поляризаційної селекції для підвищення стійкості та точності
навігаційних радіолокаційних систем у різних атмосферних умовах. Викорис-
тання статистичних методів дозволяє радіолокаційній системі адаптуватися до
мінливих умов, забезпечуючи надійність у різних сценаріях. Поляризаційна
селекція на основі статистичних властивостей поляризаційних параметрів є
перспективним методом покращення навігації в умовах підвищеної атмосфер-
ної вологості, туману та інших складних атмосферних умов і може бути вико-
ристана у розробленні сучасних систем навігації.
Ключові слова: безпека судноплавства, атмосферні умови, статистичні влас-
тивості, часткова поляризація, ехо-сигнали, радіолокаційні системи, навігацій-
не обладнання, ресурси навігаційного місткa, морський транспорт, радіолока-
ція, керованість і маневрування суден.
|
| id | journaliasakpiua-article-297376 |
| institution | System research and information technologies |
| keywords_txt_mv | keywords |
| language | English |
| last_indexed | 2025-09-17T09:26:01Z |
| publishDate | 2025 |
| publisher | The National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute" |
| record_format | ojs |
| resource_txt_mv | journaliasakpiua/ec/4023fda97cd67116954fd2c2a8d187ec.pdf |
| spelling | journaliasakpiua-article-2973762025-05-20T17:56:07Z Method of polarization selection of navigation objects in adverse weather conditions using statistical properties of radio signals Метод поляризаційної селекції навігаційних об’єктів у складних метеорологічних умовах з використанням статистичних властивостей радіосигналів Korban, Dmytro Melnyk, Oleksiy Kurdiuk, Serhii Onishchenko, Oleg Ocheretna, Valentyna Shcherbina, Olha Kotenko, Oleg safety of navigation atmospheric conditions statistical properties partially polarized echo signals radar systems navigation equipment bridge resources maritime transport radiolocation ship handling and maneuvering безпека судноплавства атмосферні умови статистичні властивості часткова поляризація ехо-сигнали радіолокаційні системи навігаційне обладнання ресурси навігаційного місткa морський транспорт радіолокація керованість і маневрування суден This research article is devoted to studying and applying polarization selection for navigation objects in difficult atmospheric conditions. It provides a novel application of Stokes parameters in radar signal processing for navigation objects, validated by experimental data. The main emphasis is on using the statistical properties of the polarization parameters of partially polarized echo signals. The article discusses in detail the statistical properties of the polarization parameters of partially polarized echo signals, which can be used to improve the accuracy of ship radiolocation systems. The study is based on analyzing experimental data collected in various atmospheric conditions. The results indicate the effectiveness of polarization selection in improving the stability and accuracy of radar navigation systems in various atmospheric conditions. The use of statistical methods allows the navigation system to adapt to changing conditions, ensuring reliability in different scenarios. Polarization selection based on the statistical properties of polarization parameters is a promising method to improve navigation in high atmospheric humidity, fog, and other complex atmospheric conditions. It can be used in the development of modern navigation systems. Присвячено дослідженню та застосуванню поляризаційної селекції для навігаційних об’єктів у складних атмосферних умовах. Основний акцент зроблено на використанні статистичних властивостей поляризаційних параметрів частково поляризованих ехо-сигналів. Детально розглянуто статистичні властивості поляризаційних параметрів частково поляризованих ехо-сигналів, які можуть бути використані для підвищення точності суднових радіолокаційних систем. Дослідження ґрунтується на аналізі експериментальних даних, зібраних у різних атмосферних умовах. Отримані результати свідчать про ефективність поляризаційної селекції для підвищення стійкості та точності навігаційних радіолокаційних систем у різних атмосферних умовах. Використання статистичних методів дозволяє радіолокаційній системі адаптуватися до мінливих умов, забезпечуючи надійність у різних сценаріях. Поляризаційна селекція на основі статистичних властивостей поляризаційних параметрів є перспективним методом покращення навігації в умовах підвищеної атмосферної вологості, туману та інших складних атмосферних умов і може бути використана у розробленні сучасних систем навігації. The National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute" 2025-03-28 Article Article application/pdf https://journal.iasa.kpi.ua/article/view/297376 10.20535/SRIT.2308-8893.2025.1.06 System research and information technologies; No. 1 (2025); 73-88 Системные исследования и информационные технологии; № 1 (2025); 73-88 Системні дослідження та інформаційні технології; № 1 (2025); 73-88 2308-8893 1681-6048 en https://journal.iasa.kpi.ua/article/view/297376/319507 |
| spellingShingle | безпека судноплавства атмосферні умови статистичні властивості часткова поляризація ехо-сигнали радіолокаційні системи навігаційне обладнання ресурси навігаційного місткa морський транспорт радіолокація керованість і маневрування суден Korban, Dmytro Melnyk, Oleksiy Kurdiuk, Serhii Onishchenko, Oleg Ocheretna, Valentyna Shcherbina, Olha Kotenko, Oleg Метод поляризаційної селекції навігаційних об’єктів у складних метеорологічних умовах з використанням статистичних властивостей радіосигналів |
| title | Метод поляризаційної селекції навігаційних об’єктів у складних метеорологічних умовах з використанням статистичних властивостей радіосигналів |
| title_alt | Method of polarization selection of navigation objects in adverse weather conditions using statistical properties of radio signals |
| title_full | Метод поляризаційної селекції навігаційних об’єктів у складних метеорологічних умовах з використанням статистичних властивостей радіосигналів |
| title_fullStr | Метод поляризаційної селекції навігаційних об’єктів у складних метеорологічних умовах з використанням статистичних властивостей радіосигналів |
| title_full_unstemmed | Метод поляризаційної селекції навігаційних об’єктів у складних метеорологічних умовах з використанням статистичних властивостей радіосигналів |
| title_short | Метод поляризаційної селекції навігаційних об’єктів у складних метеорологічних умовах з використанням статистичних властивостей радіосигналів |
| title_sort | метод поляризаційної селекції навігаційних об’єктів у складних метеорологічних умовах з використанням статистичних властивостей радіосигналів |
| topic | безпека судноплавства атмосферні умови статистичні властивості часткова поляризація ехо-сигнали радіолокаційні системи навігаційне обладнання ресурси навігаційного місткa морський транспорт радіолокація керованість і маневрування суден |
| topic_facet | safety of navigation atmospheric conditions statistical properties partially polarized echo signals radar systems navigation equipment bridge resources maritime transport radiolocation ship handling and maneuvering безпека судноплавства атмосферні умови статистичні властивості часткова поляризація ехо-сигнали радіолокаційні системи навігаційне обладнання ресурси навігаційного місткa морський транспорт радіолокація керованість і маневрування суден |
| url | https://journal.iasa.kpi.ua/article/view/297376 |
| work_keys_str_mv | AT korbandmytro methodofpolarizationselectionofnavigationobjectsinadverseweatherconditionsusingstatisticalpropertiesofradiosignals AT melnykoleksiy methodofpolarizationselectionofnavigationobjectsinadverseweatherconditionsusingstatisticalpropertiesofradiosignals AT kurdiukserhii methodofpolarizationselectionofnavigationobjectsinadverseweatherconditionsusingstatisticalpropertiesofradiosignals AT onishchenkooleg methodofpolarizationselectionofnavigationobjectsinadverseweatherconditionsusingstatisticalpropertiesofradiosignals AT ocheretnavalentyna methodofpolarizationselectionofnavigationobjectsinadverseweatherconditionsusingstatisticalpropertiesofradiosignals AT shcherbinaolha methodofpolarizationselectionofnavigationobjectsinadverseweatherconditionsusingstatisticalpropertiesofradiosignals AT kotenkooleg methodofpolarizationselectionofnavigationobjectsinadverseweatherconditionsusingstatisticalpropertiesofradiosignals AT korbandmytro metodpolârizacíjnoíselekcíínavígacíjnihobêktívuskladnihmeteorologíčnihumovahzvikoristannâmstatističnihvlastivostejradíosignalív AT melnykoleksiy metodpolârizacíjnoíselekcíínavígacíjnihobêktívuskladnihmeteorologíčnihumovahzvikoristannâmstatističnihvlastivostejradíosignalív AT kurdiukserhii metodpolârizacíjnoíselekcíínavígacíjnihobêktívuskladnihmeteorologíčnihumovahzvikoristannâmstatističnihvlastivostejradíosignalív AT onishchenkooleg metodpolârizacíjnoíselekcíínavígacíjnihobêktívuskladnihmeteorologíčnihumovahzvikoristannâmstatističnihvlastivostejradíosignalív AT ocheretnavalentyna metodpolârizacíjnoíselekcíínavígacíjnihobêktívuskladnihmeteorologíčnihumovahzvikoristannâmstatističnihvlastivostejradíosignalív AT shcherbinaolha metodpolârizacíjnoíselekcíínavígacíjnihobêktívuskladnihmeteorologíčnihumovahzvikoristannâmstatističnihvlastivostejradíosignalív AT kotenkooleg metodpolârizacíjnoíselekcíínavígacíjnihobêktívuskladnihmeteorologíčnihumovahzvikoristannâmstatističnihvlastivostejradíosignalív |