The American Journal of Engineering and Technology
41
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TYPE
Original Research
PAGE NO.
41-53
10.37547/tajet/Volume07Issue01-07
OPEN ACCESS
SUBMITED
20 October 2024
ACCEPTED
30 December 2024
PUBLISHED
30 January 2025
VOLUME
Vol.07 Issue01 2025
CITATION
Koushik Bandapadya, Md. Nurunnabi sarker, Areyfin Mohammed Yoshi,
Ashrafuzzaman Hera, & Md Omar Faruque. (2025). Global analysis of active
defense technologies for unmanned aerial vehicle . The American Journal
of Engineering and Technology, 7(01), 41
–
53.
https://doi.org/10.37547/tajet/Volume07Issue01-07
COPYRIGHT
© 2025 Original content from this work may be used under the terms
of the creative commons attributes 4.0 License.
Global analysis of active
defense technologies for
unmanned aerial vehicle
Koushik Bandapadya
Westcliff University Masters in Computer Science (MSCS)
Concentration: Software Development
Md. Nurunnabi sarker
Masters in Computer Science (MSCS) Concentration: Data
Analysis Westcliff University
Areyfin Mohammed Yoshi
MBA in Business Analytics International American University Los
Angeles, California
Ashrafuzzaman Hera
Master of Business Administration in Management Information
Systems, International American University, Los Angeles,
California. United States
Md Omar Faruque
Master of Business Administration in Management Information
Systems, International American University, Los Angeles,
California. United States
Abstract:
This paper explores active defense for UAVs
globally, with the main emphasis on detection and
countermeasure technologies. Questionnaires were
administered to 139 individuals in the USA, and the
results were analyzed with the help of the Statistic
Package for Social Sciences (SPSS), including reliability
analysis, descriptive frequency, and regression analysis.
The results concerning Hypothesis 1 concerning
technological detection impact on the adequacy of UAV
defense are the following. Analyzing the data, it was
established that detection technology influences UAV
defense significantly with F =12. 27 and a signification p,
therefore, is less than 0,001. Total regression analysis
showed that In relation to this aspect, the regression
coefficient (b = 0. 292, p <. 001) shows that detection
technology has a positive influence on UAV defense and
accounts for 8. Two percent of the total aggregated
variation across the defense effectiveness of the
participating countries (R² = 0. 082) could solely be
attributed to these potentates. Thus, the findings of
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Hypothesis 2 prove that countermeasure technology
also plays another major role in the defense of UAVs.
Analysis of variance for the model revealed that
technology used in countermeasures tremendously
impacts UAV defense with F = 113. 465, and the
calculated p is less than 0. 000; hence, the findings are
highly significant. Thus, the regression coefficient (b =
0.782, p < 0.000) indicates a significant contribution of
countermeasure technology influencing the reduction
rate, which amounts to 45 %. 14% of the variance in
UAV defense effectiveness gives a coefficient of
determination of 0.453. Based on these findings,
developing
detection
and
countermeasure
technologies are crucial to improving UAV defense
systems. The research findings suggest that azimuth
and elevation tracking and invariant pattern
recognition technologies used in this system can be
enhanced to enhance the effectiveness of a UAV
countermeasure system.
Keywords:
Countermeasure Technology, Detection
Technology, Unmanned Aerial Vehicle.
Introduction:
BACKGROUND OF THE STUDY
Unmanned Aerial Vehicles (UAVs), also known as
drones, have received an immense boost in the
adoption rates, both private and government, in the
last decade. This has, in turn, compelled research into
new ideas and innovations, hence enhancing
advancement, but at the same time, it has led to
remarkable problems and issues in security and
defense. UAVs can be used in many operations such as
surveillance, reconnaissance, logistics, and even
attack, which is dangerous to national and
internationally secured countries. This means there is
a need to create and deploy active defense
technologies to deal with these threats effectively. The
given work aims to examine the state of active defense
technologies for UAVs globally, focusing on
technological development, legislation, and strategy
usage.
UAV EVOLUTION AND DAILY APPLICATION
Technology has improved, and costs in the region have
been reduced, making UAVs accessible to everyone.
Originating from military use, UAVs are used in
multiple fields, such as agriculture, transport, relief
operations, and deliveries (Vyas, 2021). These
applications have raised concerns and stimulated the
need for strong security measures to minimize the use
by
negative
parties,
especially
in
essential
infrastructures and the military.
Threat Landscape
Terrorists or rogue individuals' use of UAVs is a complex
security threat. They can be used in spying, drug and
human trafficking, and even dropping explosives, which
makes them a proper tool for wrongdoers (Zhang et al.,
2022). Moreover, the threat is not only in one drone;
large groups of UAVs can effectively break through
traditional protection systems because of their
coordinated and controllable actions. This has led to the
creation of highly advanced defense systems that can
detect UAVs and distinguish them from other objects to
eliminate them in real time (Strohmeier et al., 2020).
Active Defense Technologies
Anti-UAV systems are the technologies that detect,
identify, and neutralize UAVs. Some technologies
include radar, radio frequency, electro-optical/infrared
detection systems, acoustics, and advanced machine
learning for threat recognition (Raj et al., 2021).
Detection and Identification
Detection and identification are the key components of
combating threats related to UAVs. New technologies
are being deployed that track small UAVs with a small
radar cross-section, and there is R.F. detection tracking,
which observes the signal exchanged between the UAV
and the operator (Rass, Jafari-Sadeghi, & Savvar, 2020).'
EO/IR sensors are perfect for quick identification, which
helps separate hostile UAVs from benign UAVs.
Integrating these systems into one detection network
improves the level of awareness in the theatre and
response time.
Neutralization
Neutralization technologies' purpose is to counter or
eliminate threatening UAVs. These are kinetic solutions
encompass the anti-drone missiles and laser systems;
non-kinetic approaches comprise the jamming and
spoofing R.F. signal control, which affects the UAV's
communication and direction system, as Dutta et
al.,(2023). Directed energy weapons and high-power
microwaves are also identified as promising means for
UAV disabling as these weapons are highly accurate and
almost non-lethal to the environment (Gonzalez et al.,
2021).
Technological Advancements
Progress in developing artificial intelligence (A.I.) and
learning has improved active defence systems. The
sensor data collected can be processed in real-time
through A.I. computation to enhance the detection rate
and minimize false alarms (Lee & Kim, 2022). Using
machine learning techniques, it will be possible to train
UAVs on different threat sources and datasets to predict
threats and, hence, constantly offer a robust defence
solution for the system.
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Regulatory and Policy Frameworks
The applications of unmanned aerial vehicle defense
technologies align with regulations and policies.
Depending on the specifics of their legislation,
governments across the globe are developing rules
concerning UAV operation and the application of
counter-UAV systems. For example, the United States
Federal Aviation Administration has set structures on
how UAVs can be incorporated into the national
airspace system while meeting security standards
(F.A.A., 2020). On the same note, EASA
–
the European
Union Aviation Safety Agency
–
has adopted elaborate
rules applicable to UAVs and defense (EASA, 2021).
However, several issues or problems are still faced in
UAV defense, even with the remarkable development
in the field. These are among the challenges; the speed
at which UAVs are continuously developing may harm
the current defense mechanisms, and global UAV
threats require a collective response to tackle them
efficiently (Smith et al., 2021). Moreover, ethical and
legal implications that pertain to some of the
countermeasures, including the kinetic and directed
energy weapons, should be well thought out (Gonzalez
et al., 2021).
Thus, the representation of UAVs in the different
sectors continues to rise and poses both prospects and
threats. UAV misuse is inevitable and thus requires
active defense technologies that will help to minimize
the impact on critical infrastructure and military
facilities. Kawohl's paper has explored prospects,
technologies, and regulations of active defense in the
present timeframe. The ability to innovate and develop
new solutions, implement appropriate policies, and
cooperate with other countries will become the most
important
factor
in
addressing
the
further
development of UAV threats.
Problem Statement
The increasing use of Unmanned Aerial Vehicles (UAVs)
in warfare and civilian life has also increased the call
for ways to safeguard against threats from the UAVs.
Other security threats that come with using UAVs
include surveillance, logistics, and even combat UAVs,
which, though they have many advantages such as
surveillance, logistics, and combat advantage, bring
along their security issues. Unauthorized UAVs can be
used for spying, same as drugs and arms trafficking, or
for a direct attack on specific targets. That is why it is
crucial to develop effective defense technologies for
identification and counteractions against such threats
(Wang et al., 2021). Classic preventive and reactive
methods as means and ways of protection are
incapable of duly responding to constantly evolving
UAV threats and, therefore, emphasize the boost of
activity in utilizing active protection systems.
Thus, this research plan is intended to provide a
comprehensive overview of the counter UAV
technologies classified as active defense systems
currently used globally. Active defense technologies are
a set of capabilities covering electronic jamming, kinetic
countermeasures, and cyber methods, also collectively
known as cyber security techniques (Zhao et al., 2022).
Through these technologies, the study aims to find out
technological modernization, best approaches, and
today’s tendencies concerning UAV threats and
measures for their counteraction.
Thus, this work is proposed to outline the current state
and the main directions for developing active UAV
defense technologies to improve awareness of the
subject. This will assist policymakers, defense planners,
and technology providers make the right choices to
improve UAV defense worldwide.
Aim of this study
This research aims to evaluate active defense
technologies targeting Unmanned Aerial Vehicles
(UAVs) globally. It ranks ICTs, examines innovations,
categorizes them, and determines their usefulness in
contexts. The present paper serves as a literature review
and focuses on delivering recommendations to improve
UAV defense systems globally.
Research Questions
RQ1
:- How is the impact of detection technology on UAV
defense effective?
RQ2
:- How is the impact of Countermeasure Technology
on UAV defense effective?
Research Objectives
RO1
:- To investigate the impact of detection technology
on UAV defense effective.
RO2
:- To investigate the impact of Countermeasure
Technology on UAV defense effective.
Rational of the Study
Both military and civil authorities extensively use UAVs;
hence, there is a need to design more enhanced defense
technologies to prevent some risks. The paper under
discussion, 'Global Analysis of Active Defense
Technologies for Unmanned Aerial Vehicles,' gives a
quantitative assessment of the efficiency of detection
and countermeasure technologies within UAV defense
systems. Two primary research objectives (ROs) guide
this study: Two primary research objectives (ROs) guide
this study:
RO1:
The state of detection technology in UAVs and its
overall effect on the concept of defense.
Detection technologies are fundamentally Put as the
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initial system of protection against UAV threats. These
are the radar systems, electro-optical sensors, infrared
sensors, acoustic sensors, and signal intelligence
systems. The success of detection technology in
identifying UAVs and tracking them from a distance is
vital before they can be threatened. Detection
technologies are thus important to be analyzed in this
study to identify their capacity and weaknesses. The
evaluation aims to determine what technical solutions
affect UAV defense efficiency in general. Aspects like
the identification range of the system, the precision of
the system, the speed of response, and the capacity to
discern UASs from other objects are evaluated. The
work aims to suggest which detection technologies
provide the best results given certain operational
scenarios.
RO2:
Technology of countermeasures to UAVs: it’s
influence on the defense capability
After an intrusion of a UAV, other countermeasure
technologies that have been developed are used to
contain the threat. These technologies cover a broad
spectrum of techniques: Electronic warfare, where the
signal is controlling and deceiving; Kinetic, where the
Interceptor, missile, and projectile are shot; Directed
energy, where laser and Microwave weapons are used;
and finally, which involves some form of trapping with
Net and drone-on-drone capture technologies.
Countermeasures involving soft-launched AS and
smaller missiles designed to carry easy-to-intercept
targets may decrease the degree of the threat,
depending on the level of accuracy, longer range, and
multi-target engagement rates. In this research, the
effectiveness of the countermeasure technologies
under investigation is intended to be assessed and
compared quantitatively in authentic operational
environments.
LITERATURE REVIEW
Unmanned Aerial Vehicles
Some of the greatest advancements in the last decade
are the Unmanned Aerial Vehicles, also known as
drones, in military, security, and delivery services.
Nonetheless, they have become immensely popular,
and they have led to a myriad of security issues. To
resolve these threats, several active defense
technologies have been developed presently all over
the world. This paper critically evaluates the current
state of active defense technologies for UAVs
concerning the level of efficiency, advancement in
technology, and prospects of implementation that are
likely to be encountered.
Active Defense Technologies
Active defense technologies for UAVs can be broadly
categorized into three groups: Established kinetic
systems, including kinetic-only systems; non-kinetic
systems; and lastly, kinetic and non-kinetic systems, also
known as hybrid systems. Kinetic systems are physical
means used to counter UAVs, including projectiles and
nets. Non-kinetic systems affect UAV operations
through electromagnetic intervention, computer
hacking, or jamming through sound. Combined systems
use part of the kinetic and non-kinetic practices,
producing better results.
Kinetic Systems
Kinetic defensive measures are one of the first counter-
UAV technologies developed at the beginning of their
use. Among them, conventional weaponry is used
against aircraft modified for UAVs, specific weapons
such as net guns, and certain UAVs whose role is to
capture the target UAV. As per the views of Karas et al.
(2021), kinetic systems are very efficient in countering
small UAVs and more efficient in areas with less impact
on the civilian population. However, they are less
effective in urban environments because of likely losses
among civilians and infrastructures.
Non-Kinetic Systems
Non-kinetic systems are considered more often because
of their accuracy and lesser consequences to other
entities. The devices include radio frequency (RF)
jammers, GPS spoofers, and directed energy weapons
(DEWs). RF jammers that interfere with the
communication channel between the UAV and the
operator are used actively in military and non-military
situations (Smith & Jones, 2022). GPS spoofers, in turn,
mislead the UAV’s navigation system, leading it in the
wrong direction or causing it to crash. High-power
microwaves and lasers are some technological DEWs
that knock out UAVs by disrupting their circuits.
Hybrid Systems
Kinetic and non-kinetic techniques are combined in
hybrid systems to increase the effectiveness of the
operations and eliminate UAV threats. For instance, a
hybrid system may employ an RF jammer to interject
with the U
AV’s communicative connection, then
transition to using a net gun to trap the UAV physically.
Miller and Adams (2021) observe that using hybrid
systems is more likely to succeed when the environment
is challenging or when one technique plan will not work.
Challenges and Limitations
However, the following are some difficulties and
disadvantages that limit the use of active defense
technologies today: One of the most important
problems is the dynamics of developments within the
UAV industry. Currently, UAVs are advanced to include
functionalities regarding self-navigation and anti-
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interference capabilities, which also translate to being
difficult to counter (Wang & Chen, 2022). Thus,
counter-UAV technologies must be enhanced step by
step to prevent any new risks from appearing.
Legal and ethical issues are also among the most
important limitations to consider when conducting an
analysis. People get worried when kinetic systems are
installed in urban society because of collateral damage
and
insecurity.
However,
some
non-kinetic
approaches, such as RF jamming, may affect genuine
communication systems due to the possession of
unlawful frequencies (Smith & Jones, 2022). These
problems require the creation of certain legal bases to
regulate counter-
UAV technologies’
deployment
properly.
Many countries have deployed active defense systems
against UAVs, mainly due to their increased use by
terrorists. In the USA, DoD has also dedicated fairly
good resources to the procurement and deployment of
counter UAV systems, mainly for protecting
installations and assets. An example is the Counter-
Rocket, Artillery, and Mortar (C-RAM) system, which
was used for intercepting UAVs (Miller & Adams,
2021).
Even in Europe, its member countries, such as the UK
and Germany, have also developed their counter-UAV
technologies. The UK uses multiple systems, such as
Skyfall, which employs a net gun, and Drone Dome, an
RF jamming system (Karas et al., 2021). Meanwhile,
Germany has engineered AI and ML into its respective
counter-UAV systems for better detectability and
interception (Brown et al., 2023).
Asia, China, and Israel are leading countries developing
modern counter-UAV systems. China has also
purchased directed energy weapons and an automatic
detection system, while Israel’s Iron Dome h
as been
modified to address UAV threats (Wang & Chen, 2022).
The mentioned countries have proved that adopting
various technologies that counter the dynamic UAV
menace is possible.
Detection
Technology
and
UAV
Defense
Effectiveness:
Some of the contemporar
y scholar’s research findings
indicate a progressive advancement in UAV detection
systems. Radar, Radio Frequency (RF) detection,
electro-optical (EO) and Infrared (IR) sensors, and
Acoustic sensors form the core parts of technologies in
use now. For example, radar capabilities have been
improved to distinguish little UAVs at a further
distance and with higher precision. Liu et al. (2021) also
pointed out that modern radar systems can still
distinguish a UAV from other flying objects, such as
birds, with the help of the Doppler signatures relating
to the specific flight of a UAV. Likewise, RF detection
systems, which continuously track the UAVs’
communication signals with their respective control
units, have also been developed more sophisticated to
jam and decode these signals in bodily spectral crowded
conditions (Gupta & Kumar, 2022). EO and IR sensors
offer vision and heat input, which can be further
analyzed with the help of artificial neural networks to
detect UAVs with high accuracy (Zhang et al., 2023).
However, the following challenges are still experienced
in the detection of UAVs. A problem with small UAVs is
low Radar Cross section, which prevents small UAVs
from being detected by conventional radar equipment.
Also, UAVs fly at low heights and speeds, making
detecting them even more challenging. Thus, Zhang et
al. (2023) observed that false alarms interfere with
reliable detection due to clutter from buildings,
vegetation, and other objects on the ground. Further,
the control signals can be avoided by using encrypted or
frequency-hopping communication since RF detectors
find it hard to intercept them (Gupta & Kumar, 2022). It
was established that although acoustic sensors are
useful in certain circumstances, their effectiveness is
reduced with environmental noise and the short range
of identification, especially in an urban setting (Liu et al.,
2021).
Integrating multiple detection technologies into a
cohesive system has been proposed to enhance the
effectiveness of UAV defense. Multi-sensor fusion,
which combines data from radar, RF, EO/IR, and
acoustic sensors, can provide a more comprehensive
and reliable detection capability. This approach
leverages the strengths of each technology while
mitigating their weaknesses. For example, a study by
Zhao et al. (2020) demonstrated that a multi-sensor
fusion system could achieve higher detection accuracy
and lower false alarm rates than single-sensor systems.
The integration of machine learning algorithms further
enhances this capability by enabling real-time analysis
and classification of detected objects, thereby
improving the overall effectiveness of UAV defense
systems (Wang et al., 2021).
The effectiveness of UAV defense systems depends not
solely on detection technologies but also on the ability
to neutralize identified threats. Kinetic and non-kinetic
countermeasures are employed to this end. Kinetic
measures, such as anti-aircraft guns and missiles, are
effective but can pose significant risks, particularly in
urban environments. Non-kinetic measures offer safer
alternatives, including jamming, spoofing, and directed
energy weapons. Jamming disrupts the communication
link between the UAV and its operator, causing it to lose
control and potentially crash (Rahman & Saeed, 2022).
Spoofing involves:
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•
Sending false signals to the UAV.
•
Taking control away from the operator.
•
Directing the UAV to a safe location.
Directed energy weapons, such as high-powered
lasers, can turn off UAVs by damaging their electronic
components (Cheng et al., 2021). Integrating these
countermeasures
with
advanced
detection
technologies creates a layered defense system,
significantly enhancing overall effectiveness.
Thus, future work seeks to continue the investigations
of UAV detection and defense solutions, overcoming
the current limitations. It is anticipated that
improvements in algorithms for signal analysis and
machine learning will increase the detectability and
decrease the number of false alerts. Quantum radar and
newer materials for EO/IR are also expected to help
solve problems in challenging terrains (Zhang et al.,
2023). Furthermore, increased use of artificial
intelligence (AI) in UAV defense systems is expected to
enhance the identification of threats and their
elimination faster and with increased accuracy. Since
UAV technology is actively developing, the systems for
detecting and combating their possible threats should
also be improved. Governments, together with
industries and academia, will play corresponding roles
in achieving this enhancement and protection of
airspace from unauthorized or malicious UAVs (Wang et
al., 2021).
METHODOLOGY
Theoretical Framework
Hypothesis Development
H1
:- There is a significance impact of detection
technology on UAV defense effective.
H2
:- There is a significance impact of Countermeasure
Technology on UAV defense effective.
RESEARCH PHILOSOPHY
The positivist theoretical framework is well-suited for
accomplishing this purpose. The researcher may gather
and analyze quantitative data using systematic surveys,
questionnaires,
and
statistical
analysis
while
maintaining a positivist perspective. This method is
especially beneficial for studying intricate social
phenomena, like the global analysis of active defense
technologies for unmanned aerial vehicles (UAVs) in
the USA. By employing structured data collection
techniques, the researcher can objectively measure
and evaluate the effectiveness and deployment of
various UAV defense technologies. The positivist
approach ensures that findings are based on empirical
evidence and statistical rigor, providing reliable and
generalizable insights. This is crucial for informing
policy decisions, technological development, and
strategic planning in UAV defense.
RESEARCH APPROACH
The researcher was with expected conclusions
regarding the hypothesis based on the factual data.
Consequently, in this investigation, only the deductive
approach is used. Since the researcher’s dat
a collection
would not contribute to formulating new insights or
paradigms, an inductive methodology should not be
applied (Theophilus, 2020). The deductive method
enables testing hypotheses based on prior assumptions
of a theory, given the analysis of specific data. This
approach applies rigor and gets to the point instead of
trying to come up with relatively novel theories and
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concepts.
METHODOLOGICAL CHOICE
The classification of methodological choices can be in
terms of quantitative, qualitative, and mixed method
classifications. This research used a quantitative
analytic approach to examine the global active defense
systems market for UAVs, focusing on the USA. This
objective was pursued with systematic and
standardized data collection and quantitative
evaluation of UAV defense technologies to provide an
accurate assessment and analysis.
RESEARCH STRATEGY
Selecting a survey as the main data collection method
has several benefits in this study. Surveys are very
suitable and effective for obtaining information from
many people simultaneously. However, their efficiency
in terms of time and money enables the researcher to
collect a relatively large amount of data within a short
time. Survey data can, therefore, be quantized and
quantified into variables for easy comparison and
analysis using statistics to determine relationship
coefficients.
Data Collection Method
Primary research was done through an extensive
questionnaire prepared by recognized leaders in the
defense sector that covered the global assessment of
active defense technologies for UAVs. It produced a set
of data that was comprehensive enough to generate
statistical analysis and pattern recognition. The sources
used in the research were participants from the USA's
defense industry. A self-administered Google Forms
survey was conducted and posted on social media
platforms like LinkedIn and Facebook for maximum
coverage and response. The total sample size was 139,
contributing to a rich analysis dataset. This approach
helped cover a wide spectrum of ideas and experiences,
adding to the credibility and cross-checking of the
findings regarding the efficacy and incorporation of
different active defense systems into UAVs.
DATA ANALYSIS
The statistical package referred to as the SPSS is
acknowledged for its effective processing and
organizational structure. The author noted that it is
useful in handling large and complex data and
performing complex statistical computations (Daniel,
2014). The researcher needs access to the software to
conduct a detailed examination of the collected data
for this study. To assist with its interpretation, the data
shall be presented in tables and graphs using software
known as SPSS. The survey findings were analyzed using
classical statistical methods like mean and median,
regression, t-test, and descriptive analysis. This tool is
very helpful regarding the present work, as it aids in
simplifying the text and thus helps the reader to absorb
the knowledge presented. After data collection, an
analysis will be done according to the guidelines of this
particular study area of concern. Administration of the
data sheet involves entering it into the SPSS program
and administering several tests before proceeding with
the analysis. These include Descriptive statistics,
Regression and Correlation, and Reliability analysis. By
following through this, the research questions will be
answered in the right manner. Data analysis can only
proceed after these steps are accomplished, which
assures the findings are valid and relevant to the study's
objectives.
Ethical Consideration
The research was thoroughly explored the ethical
concerns specific to each academic discipline. After
ensuring that the participants have been thoroughly
informed about all the crucial aspects of the inquiry,
they were requested to grant their informed consent
for the research to move forward. If the study is
completed and participants choose to withdraw their
replies after data processing, their responses will be
excluded from the analysis. Your information will be
handled with utmost care and kept secure at all times.
Only the researcher who submitted the request and the
system administrator will have access to the data.
Throughout the procurement and examination of data
for this investigation, utmost importance was placed on
upholding ethical principles. Recognition was given to
the voluntaries' right to make their own decisions, and
they were provided with the necessary information
before giving consent. We are confident that the study
data we have provided were assist you in developing an
appropriate response. In addition, steps have been
taken to ensure the reliability and confidentiality of the
data. The researcher was accessed to any data or
information that could be used to establish contact
with a participant. We have taken extensive measures
to ensure the utmost confidentiality of the research
findings. The researchers' commitment to upholding
ethical principles is praiseworthy.
RESULTS/FINDINGS
Demographic Analysis
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Table Gender Frequency
The above table shows the gender frequency of the participants who filled out the questionnaire for this study.
The 71 male participants had a frequency of 51.1 %, and the 68 female participants had a frequency of 48.9 %.
Table Age Frequency
The distribution of age in a specific population involves 139 people. Out of the respondents, the largest proportion
is within the 35-45 age range, with a total of 39 respondents, followed by the 25-35 age range, with 38
respondents. The smallest is the age category 18-25, comprising only 25 members. The age group of more than
46 accounts for 37 research participants. This distribution shows that the different groups' ages are quite average,
with slightly more people in the 35-45 and 25-35 age range. These frequencies give ideas about the sample's
demographic characteristics that may be useful for different analyses and interpretations.
51%
49%
GENDER
18-25
18%
25-35
27%
35-45
28%
Above 45
27%
AGE GROUP
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Reliability Analysis
Table Reliability Statistics
Variables
Cronbach's
Alpha
N of
Items
Detection Technology
0.898
5
Countermeasure Technology
0.803
5
UAV Defense Effective
0.900
5
The analysis conducted here helps identify the validity and reliability of the research variables. Cronbach’s alpha,
one of the most oft-used methods for reliability analysis, compares the
sum of the variances and covariance’s of
the items utilized for constructing the instrument to the total variance. A higher value of Cronbach’s alpha, closer
to 1, represents higher reliability and internal consistency of the items that define the variable of interest.
In this research, the Detection Technology variable has acceptable reliability with a Cronbach’s alpha of 0.898 on
five scale items. Likewise, the Countermeasure Technology variable shows excellent reliability with a Cronbach’s
alpha of 0.803, derived from 5 items. At the same time, the UAV Defense Effectiveness variable can boast a quite
reasonable inter-
item reliability estimate of Cronbach’s alpha 0.900, measured with the help of 5 items. These
results clearly show that the items for each variable successfully measure the qualities that are supposed to be
assessed validly and consistently, establishing the reliability of this study’s instrument.
Regression
Hypothesis 1
st
: - There is a significance impact of detection technology on UAV defense effective
Table Model Summary of Hypothesis 1
st
The outcomes in this table indicate the R-value, R square, and adjusted R square value. These quantitative values
vary between 0 and 1 and can be best described as a model fit. The second condition that should be fulfilled
means that the R-value is always bigger than the R square value. Here, the R-value equals 0. 287, which is much
higher than the R square value of (0.082), thus an appreciable model fit. Also, the adjusted R square value of
(0.076) is very much equal to the R square value (0.082), as a result of which the model's mounting efficiency is
effectively proven.
Thus, the following indicators show that the model is fit and acceptable. More detail, they demonstrate how the
detection technology influences the defense against UAV devices. The R-value indicates the reasonable level of
the technology's correlation with the given subject; the R square and adjusted R square values show that a portion
of the variance in UAV defense effectiveness can be attributed to the detection technology variable.
Table ANOVAa of Hypothesis 1
st
The results of this test suggested that detection technology is a large factor in how effectively UAVs can be
defended against. The first hypothesis was tested by regressing the main dependent variable, UAV defense
effectiveness, against the predictor variable, detection technology. Detection technology plays a paramount
important role in the determination of UAV defense, F (12. 27), p < 0. 001 with the regression coefficient value
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showing the percentage contribution of detection technology towards UAV defense; (b = 0. 292, p < 0.001). The
data provided in these results portray the relevance of detection technologies to the efficacy of UAV defense.
Additionally, a high coefficient of determination was indicated by the R² value of 0.082. The model's coefficient of
determination or R2 value is 0.082, which implies that the independent variables in the present model explain 8.2
% of the variability of the dependent variable. This discovery supports the notion that detection technology has a
positive effect on the indicated aspect of UAV defense, implying that detection technology enhancements can
significantly enhance the overall UAV defense framework.
Hypothesis 2
nd
: - There is a significance impact of Countermeasure Technology on UAV defense effective.
Table Model Summary of Hypothesis 2
nd
Model
R
R Square
Adjusted R
Square
Std. Error of
the Estimate
1
.673
a
0.453
0.449
3.18749
The outcomes in this table, which highlight the R-value, R square, and adjusted R square values, are of significant
importance. These quantitative values, ranging from 0 to 1, are crucial in determining the model fit. The second
condition, where the R-value is always greater than the R square value, is a key aspect to consider. In this instance,
the R-value is 0.673, significantly higher than the R square value of 0.453, indicating a commendable model fit.
Furthermore, the adjusted R square value of 0.449, which is very close to the R square value of 0.453, further
validates the model's increasing efficiency.
Therefore, the following indicators reiterate the model's fitness and acceptability, providing a sense of
reassurance and confidence in the research findings. In more detail, they demonstrate how the countermeasure
technology influences the defense against UAV devices. The R-value indicates the reasonable level of the
technology's correlation with the given subject; the R square and adjusted R square values show that a portion of
the variance in UAV defense effectiveness can be attributed to the detection technology variable.
Table ANOVAa of Hypothesis 2
nd
The results of this test suggested that countermeasure
technology is a large factor in how effectively UAVs can
be defended against. The first hypothesis was tested by
regression of the main dependent variable, UAV
defense effectiveness, against the predictor variable,
countermeasure
technology.
Countermeasure
technology is paramount in determining UAV defense,
F (113.465), p < 0. 000 with the regression coefficient
value showing the percentage contribution of
countermeasure technology toward UAV defense (b =
0. 782, p < 0.000). The data provided in these results
portray the relevance of countermeasure technologies
to the efficacy of UAV defense. Additionally, a high
coefficient of determination was indicated by the R²
value of 0.453, which implies that the independent
variables in the present model explain 45.3 % of the
variability of the dependent variable. This discovery
supports the notion that countermeasure technology
positively affects the indicated aspect of UAV defense,
implying
that
countermeasure
technology
enhancements can significantly enhance the overall
UAV defense framework.
CONCLUSION
Summary
This research is based on a global analysis of active
defense technologies of UAVs; the research findings
strongly suggest that this market is expanding due to
innovations and, more importantly, the rising
importance and commonality of UAVs in various
spheres of life, including military and peace purposes.
This is why effective countermeasures are necessary to
deal with the possible dangers of unauthorized or
hostile UAVs. They, together with the subsequent
points of discussion in this present study, can arrive at
the following conclusion:
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Key Findings
Technological Diversity: The discussion highlights a
continuum of active defense systems, from electronic
interference and deception to kinetic engagement and,
finally, laser-based weapons. Each has a different set of
benefits and drawbacks, and effectiveness depends on
the operation's characteristics and the nature of the
UAV threat.
Effectiveness of Detection and Countermeasure
Systems: This again shows how it is not feasible to
separate
the
detection
system
from
the
countermeasure system when dealing with UAVs.
Modern radar, optical, and acoustic are primary
components in early detection, while machine learning
algorithms can help with targets' identification and
threat assessment. Synchronizing detection capabilities
with countermeasure responses substantially enhances
the defense system's dependability.
Regulatory and Ethical Considerations: The use of
active defense technologies is a problem in terms of
regulation and ethics. Security of infrastructures, on the
one hand, and protection of individuals' rights and
possible civilian loss, on the other hand, should be
considered. In this context, the need arises for global
collaboration and harmonized rules on using such
technologies.
Adaptability to Emerging Threats: UAV technology is
constantly improving in various aspects, such as stealth,
speed, and agility. Thanks to this, active defense
systems need to be elastic to efficiently oppose these
new threats. The study also raises concerns about the
need to conduct further research to advance the ever-
evolving UAV field.
Implications
Military Applications: AE solutions are important in
military use, which aims to protect assets and people
from hostile UAVs. Notably, options to quash potential
threats fast and efficiently can contribute to the overall
improvement of combat space orientation and
operation security.
Civilian Infrastructure Protection: In civil applications,
the protection of infrastructures like airports, power
plants, and events such as the UAV menace is a growing
concern. Establishing proper defense measures might
prevent threats and boost the level of security.
Commercial UAV Operations: As the use of commercial
UAVs rises, there are more opportunities for accidental
or malicious interference. Active defense technologies
can complement securing UAVs and allow integration
into the NAS.
Economic Impact: Active defense technologies already
impact the economy through development and
deployment. Advanced defense systems are needed
around the world, and the need for these systems
contributes to the development of the defense and
aerospace industries. This means that investment in
this sector can push innovation and contribute to the
development of economies.
Limitation of the Study
Based on the global analysis of active defense systems
for UAVs, some benefits and drawbacks of this research
can be identified. So, the directions and approaches
explored in the present papers give valuable insights
into the current state and possible trends in active
defense technologies for UAVs. Such limitations affect
the generality and usefulness of study conclusions on
the one hand but indicate directions for future research
and enhancement on the other hand.
Scope and Generalizability
The paper does not concentrate on individual systems
and their engagement within particular scenarios, but
it introduces the concept of active defense throughout
a wide array of systems. Therefore, the cross-
environmental and cross-threat generality of the
results may be rather limited. Current research pointed
out that some of the following parameters may highly
influence the performance of a certain defense
technology: geographical environment, sophistication
levels of UAV threat, and specific operations required.
Subsequent research might be useful in analyzing these
variables more precisely by employing other controlling
techniques.
Rapid Technological Advancements
This is an area of development in UAV technology and
corresponding defenses, whether advertised or
deployed. Technological progress in the field
introduces many new findings, rapidly retiring prior
data and analysis. One limitation of the study is that the
study is conducted based on current technology, and
the advancement of technology that occurs in the
future may need to be fully included. Specifically, it is
essential to regularly monitor and update to keep it as
topical and correct as possible. The use of real-time
data and a forecasting model would be beneficial in
identifying potential future changes and technological
advancement.
Data Availability and Reliability
In this area, one of the key problems is the need for
uninterrupted and high-quality access to the necessary
data sources. Several defense technologies and UAV
capabilities are secret or commercial; so much
information regarding their advancements is scarce.
The above restriction can lead to a lack of information
about the prospects and constraints of some
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technologies. First, the evaluation is confined to
published studies, which might include only studies
with positive outcomes and could be subject to bias or
inaccuracy. The report could get more credible sources
of data and information from the industries and other
military organizations for efficient collaboration.
Regulatory and Ethical Considerations
The study touches on regulatory and ethical issues but
needs to explore these aspects in depth. Deploying
active defense technologies raises significant ethical
questions, such as the potential for collateral damage
and privacy concerns. Additionally, the regulatory
landscape for UAVs and their defense varies widely
across different jurisdictions, complicating the
implementation of standardized solutions. A more
comprehensive analysis of these regulatory and ethical
considerations would provide a fuller picture of the
challenges in deploying these technologies.
Interdisciplinary Integration
Effective UAV defense requires the integration of
various technological, operational, and strategic
disciplines.
The
study
primarily
focuses
on
technological aspects, potentially overlooking the
importance of human factors, organizational dynamics,
and strategic decision-making processes. Future
research should adopt a more interdisciplinary
approach, incorporating insights from human factors
engineering, organizational behavior, and strategic
management.
Future Directions
Enhanced Integration and Automation: Further studies
should be conducted on optimizing the coordination
and utilization of detection and countermeasure
systems and robotics technology. Applying artificial
intelligence and machine learning can enhance system
sensitivity and flexibility, aiming to counter threats in
real-time.
Collaboration and Standardization: International
cooperation and unification of defense technologies
and agendas concerning UAVs are imperative to tackle
global threats. When this knowledge and resources are
shared, the development of these defense solutions is
faster, and their correct and legal use is guaranteed.
Focus on Emerging Technologies: One cannot
overemphasize the need to pursue research on other
new technologies, including high-energy lasers and
EMP weapons. These technologies offer the potential
to improve the efficiency and accuracy involved in
neutralizing UAVs, thereby minimizing the impacts on
innocent lives.
Public Awareness and Education: Thus, it is essential to
increase public awareness of the opportunities and
threats connected with UAVs and their defense
advantages. Education interventions such as seminars
and awareness campaigns on the use of UAVs can help
raise general public awareness of the security
challenges in UAVs and stimulate debates on regulatory
and ethical considerations for UAVs.
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