Abstract
The rapid development and proliferation of drone technology have led to an increase in various threats. In particular, the number of attacks, crimes, and accidents using drones is continuously expanding, and the need for a systematic response is growing. Existing response strategies have mainly focused on real-time defense-oriented technologies and policies, such as detection, identification, and neutralization of drones. However, recently, the importance of drone forensics, which identifies the flight path of drones, pilot information, and the cause of accidents after an incident, has been highlighted. Drone forensics combines elements of traditional digital forensics and non-digital (physical) forensics, and live forensics technology that collects and analyzes data immediately after an incident plays a crucial role. Drone forensics has distinct technical characteristics compared to general forensics, and this study presents a systematic analysis framework and analysis algorithm structure that reflects these technical characteristics and convergent analysis factors. It comprehensively reviews the major drone forensics technologies currently being utilized. This will help to secure the legal evidence capability of drone forensics and increase its usefulness as evidence.
Keywords: Drone forensics, UAV analytics, Digital forensics, Artificial intelligence, Live forensics, Drone threats
Highlights
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Proposes a hybrid drone forensic framework combining live, digital, and physical data
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Introduces a sequential forensic algorithm tailored to UAV-specific evidence
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Analyzes key forensic technologies for crash cause and pilot identification
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Addresses legal admissibility of forensic drone data
1. Introduction
1.1. Background and need for the study
1.1.1. Expanding the drone threat
Drones are emerging as a key strategic asset in military operations, as evidenced by the recent conflict between Russia and Ukraine. Initially used primarily for reconnaissance and surveillance purposes, drones have evolved into combat weapons capable of precision strikes and are becoming an essential force in modern warfare [1,2]. In addition to these military applications, drones have a wide range of civilian and commercial uses, including public safety, industrial inspection, logistics and transportation, agricultural monitoring, and broadcast filming. The technology and industry continue to grow. However, as the use of drones has proliferated, so have the number of terrorist, criminal, accidental, and illegal intrusions, and the threats posed by drones have become more sophisticated and diversified. In this context, the importance of ∗∗drone forensics∗∗, which analyzes drones to secure forensic evidence and identify flight records, pilot information, and technical defects, is becoming increasingly prominent (see Fig. 5, Fig. 6, Fig. 7, Fig. 8, Fig. 9).
Fig. 5.
Drone surface evidence detection.
Fig. 6.
Flight data using public code (PX4, ArduPilot).
Fig. 7.
Private code flight data (DJI).
Fig. 8.
Drone forensics program (source: MD-drone).
Fig. 9.
Drone destruction and data integrity experiment with firearms.
1.1.2. The importance of drone forensics
As drones are increasingly used not only as weapons of war but also as tools for everyday crime and public safety threats, the way we respond to drones must change. Previously, technologies and policies have focused on real-time responses, such as detecting, tracking, identifying, and neutralizing drones, but these are limited in their ability to eliminate the underlying threat. Especially in incidents involving illegal drone intrusions, filming, drops, and hacking, post-mortem analysis and evidence collection are critical to identifying the root of the threat and improving future response strategies.
These post-mortem activities are performed through a drone forensics system that converges various technologies such as digital forensics, video analysis, sensor data interpretation, and tracing of wireless communication records, and requires an integrated approach to detection, response, and analysis, just as criminal investigations must work in conjunction with prevention and on-site apprehension.
1.2. Research objectives
1.2.1. Defining the drone forensics concept
Review the main contents related to drone forensics by defining the concept of drone forensics and identifying the commonalities and differences with general forensics. Based on this, a comprehensive system related to drone forensics can be established. Drone forensics has distinct characteristics from general forensic techniques and often requires the use of various forensic techniques in conjunction with one another. Therefore, it is necessary to establish a comprehensive concept and system that takes these points into account.
1.2.2. Organizing drone forensics systems and algorithms
Depending on the characteristics of drone forensics, an execution algorithm is required that takes them into account. Drone forensics algorithms can differ from general forensics algorithms, and there are specific aspects that need to be considered and reviewed at each stage of execution. Therefore, it is necessary to analyze these points in order to construct a comprehensive drone forensics algorithm.
1.3. Methodology and organization
1.3.1. Research methods
This study was conducted as a case study related to drone forensic technology that has been developed or is currently being developed.
1.3.2. Configure
This study analyzes drone threats, which are expanded upon in Chapter 2. Chapter 3 analyzes explicitly a drone forensics system and algorithms to improve provability and evidential value based on characteristics related to drone forensics, and reviews the direction of technological development. Finally, Chapter 4 summarizes the study's findings.
2. Theoretical background
2.1. Drone evolution and scaling
2.1.1. Drone industry development and expanding uses
Drones were initially developed for military purposes, but have evolved significantly as they have expanded into the civilian realm. Drones have become increasingly popular as the technology has improved and become more affordable and user-friendly. Early drones were armed UAVs used by the United States, the United Kingdom, China, Iran, and others [3], but have recently expanded into modern roles in a variety of sectors, including commerce, agriculture, environment, energy, and surveillance [4] The civilian drone market was valued at approximately $10.55 billion in 2024 and is expected to reach $49 billion by 2033 (CAGR: 18.6 %) [5] Military drones are also expected to grow from $24.2 billion in 2025 to $56.69 billion in 2033 (CAGR of 11.2 %) [6] and the related market is continuously growing. As the number and purpose of drones increase, so do the associated threats.
2.1.2. Key technologies and advances in drones
Drones are a combination of different technologies, including mechanical, chemical, and SW technologies. To consider drone forensics, it is necessary to understand the technical and mechanical features of drones. The main technologies involved in drones include the following.
The technologies in Table 1 are the core technologies associated with drones. Drones utilize a range of the latest technologies, including materials, batteries, cameras, software, sensors, and communication methods, and these technologies are gradually becoming more specialized for drones, unlike in the early days. The early DJI Mavic models utilized GoPro cameras, but the latest DJI Mavic 4 Pro features a 360-degree rotating camera, which is a relatively rare design choice. As a result, the development of drone-specific technologies, including materials, batteries, cameras, and communication methods, is increasing. These technologies are continually being developed to make them smaller, lighter, more efficient, and autonomous [7]. Moreover, there are limitations in utilizing existing analysis methods for these drone-specific technologies.
Table 1.
Key technologies related to drones.
| Item | Key technologies and purposes |
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| Material |
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| Propulsion Technology |
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| Battery |
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| Fuel |
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| Camera |
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| Flight Controller (FC) |
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| Communication |
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| Software |
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| Sensors |
|
2.2. Expanding the drone threat
Drone threats can be categorized into three main categories. They can be categorized according to the purpose of the flight, the type of damage, and the operator's intent. Drone threats can be categorized into drone attacks (drone terrorism), drone crimes, and drone accidents.
2.2.1. Drone attacks
This refers to offensive drone threats. This can be anything from guerrilla attacks using drones, to terrorist attacks against individuals or facilities, to full-scale military attacks. Some studies have identified 76 confirmed cases of drone use by terrorist organizations from 2016 to 2019 alone, with 50 people killed and 132 injured in these attacks [8], and the number of such attacks is expected to increase. Drone attacks can range from highly sophisticated and expensive equipment built for military purposes to simple drones built or modified by individuals. Drone attacks can be used to deliver explosives, conventional, chemical, biological, radiological, and nuclear weapons [8] and network penetration [9]. Drone attacks can be classified in various ways, such as whether they are public, targeted at individuals or facilities, classified according to the method of attack, and classified according to the scale of the attack, and various attacks are possible depending on the type of aircraft, method of attack, and type of weapon, as shown in Fig. 1.
Fig. 1.
Drone weapon system.
2.2.2. Drone crime
It refers to the use of drones for criminal purposes. There are cases of using drones for existing crimes, such as theft, residential invasion, illegal filming, prison smuggling, and illegal surveillance. Additionally, there are cases of violating laws and regulations related to drones, including flying in a no-fly zone, violating control methods, and operating unregistered aircraft. In general, criminal offenses include the use of drones for sexual purposes, the use of drones to photograph military facilities, and the use of drones to smuggle drugs, smuggle goods into prisons, and monitor police activities [10]. Criminal offenses related to drones include violating no-fly zones, disregarding flight laws, and failing to comply with registration obligations, with regulations varying slightly by country.
2.2.3. Drone accidents
This occurs when damage results from unintentional negligence while using a drone (see Fig. 2). Just like car or airplane accidents, drones can also have various accidents during operation, which can be caused by human factors such as pilot negligence or inattention, airframe defects, natural influences such as jamming or interference, strong winds, low battery, collision with animals such as birds, etc. [11]. Many drones are crashing for various unfortunate reasons during flight, and the causes are being analyzed from environmental, human, and technical perspectives [[12], [13], [14]]
Fig. 2.
Drone threat response system.
2.3. Drone response system
2.3.1. Drone response framework
A typical drone response plan might look like this.
Drone detection refers to the process of identifying the presence of a drone. It is necessary to detect whether a drone is in flight and to distinguish it from other airplanes or animals, such as birds. There are RF, acoustic, and non-electrical methods for drone detection, each with its own advantages and limitations, depending on the situation [15]. Drones are difficult to detect due to their size and flight characteristics, making it challenging to recognize them even at a certain distance [16]. Drone radar or surveillance devices require high costs, have blind spots, and are prone to false alarms due to bird lights.
Drone identification refers to recognizing and obtaining information about the detected drone's aircraft and pilot [17]. It is necessary to identify whether the flying drone is a registered, friendly, authorized, civilian, or military aircraft. The outcome of this identification will determine whether a response is warranted.
On-Site Response: This is a direct response to the threatening drone. In general, there are two types of countermeasures: hard-kill using projectiles and directed energy weapons [18] and soft-kill [19] that subdue or capture unauthorized drones without physical destruction, and various countermeasures such as anti-drone guns, radio jamming devices, and net guns are available for this purpose.
Analysis: It is a field that acquires relevant information from captured or crashed drones [20]. For unregistered or unidentified drones, various data, such as flight path, altitude, and photos, are checked and analyzed. In the case of a crashed drone, the cause of the crash is estimated [21].
These drone responses are organically organized and will have a significant impact on the next phase of each response.
2.3.2. Limitations of drone response systems
The market for counter-drone technology continues to grow, and the technology is evolving rapidly. The antidrone market, valued at $2.31 billion in 2024, is projected to reach approximately $26.26 billion by 2033, expanding at a compound annual growth rate (CAGR) of 27.52 % [22]. Various antidrone studies are examining intidrone technologies in three phases: detection, identification, and neutralization [[23], [24], [25]], identification using artificial neural network technology [26], drone detection, integration of passive surveillance technology for detection and jamming [27], spoofing [28] anti-drone laser technology [29] physical countermeasure technology [30], etc. are being developed. However, the field of drone forensics has been somewhat neglected in various drone countermeasure systems and technical studies. Although various anti-drone technologies are being studied, they have several limitations, including cost, technical efficiency, and environmental concerns. From this perspective, forensics, which involves the post-mortem analysis of drones, is becoming increasingly important.
3. Drone forensic systems and forensic algorithms
3.1. Definition and characteristics of drone forensics
3.1.1. Definition of drone forensics
Forensics is the application of scientific methods and procedures to the solution of crimes and legal investigations [31]. It refers to a variety of disciplines that support the criminal justice system [32], encompassing a wide range of scientific methods and techniques used to collect, analyze, and present evidence in a legal context. Gathering evidence related to a crime is essential in the modern justice system, and the importance of forensics continues to be emphasized [33]. Forensics is constantly expanding in scope, from general forensics, including fingerprints, DNA, bloodstains, microscopic evidence, and ballistics, to biology and chemistry, psychology, psychiatry, digital forensics, and forensic science. Drone forensics can be defined as “the techniques and procedures for collecting a variety of forensic evidence from drones.” The nomenclature can be confusing because general forensics, such as DNA, psychology, and digital forensics, refer to specific techniques, whereas drone forensics focuses on drones.
3.1.2. Characteristics of drone forensics
Drone forensics is unique in that drones are digital airplanes.
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Moving object: Drones are not stationary like computers and other digital devices, but are characterized as moving objects. Since drones are intended to fly, they have various equipment and configurations for flight, and depending on these characteristics, various physical traces are left on the drone. The primary traces can include fingerprints, DNA, and microscopic evidence, and depending on the type of propulsion power, physicochemical evidence such as gasoline may be left. In particular, the drone is often handled or forced to change batteries, which can leave evidence on the surface of the drone's fuselage. In tests on common surfaces such as metal and plastic, about 30 % of DNA evidence was detected.
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Generated data: Drones are intended to fly and collect various aerial data, such as altitude and route. Some data is stored, but some is volatile and disappears after the flight, which varies by manufacturer. The data generated by drones can be collected in various ways, and the information provided may vary depending on the type of aircraft and manufacturer. However, it is essential to check the flight path to determine the overall flight path, origin, and destination of the drone. Flight data is important information for determining whether the aircraft is defective or the cause of the crash.
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Storage method: Drones are digital devices that collect and store various digital data. Data is stored internally (FC) or externally (SD card). Flight data, including flight path, altitude sensor value, and tilt, is often stored in the internal memory, while photos and videos are typically stored in the external memory. The information stored varies depending on the manufacturing method, and there are also differences among manufacturers. Open-source-based manufactured drones can often extract the original data, but manufacturers such as DJI often provide processed or encrypted data instead. In such cases, the reliability of the data may be somewhat limited, as you must use the manufacturer's provided application. The data can be used to estimate a route based on where and when it was taken.
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Data Distribution: Drones often have simultaneous or distributed data stored on the controller, the aircraft, a smartphone, and the ground control center. This can vary depending on the type of drone and its operation, and it is necessary to check the data from the drone itself, the controller, and the smartphone to verify accurate information.
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Live data: Drones can collect different data when they are in flight (operating and communicating with the controller) and when they are not, and it is often necessary to collect data during flight. Therefore, unlike general devices, it is important to collect data when drones are in flight, and the need for live forensics increases compared to general digital devices.
These characteristics necessitate a complex set of forensic procedures and methods that differ somewhat from those used for typical computers or fixed objects.
3.2. Review drone forensics framework
Fig. 3organizes drone forensics, and it is essential to note the following points when comparing them to general forensics. First, drone forensics must consider both on-site forensics (including physical and chemical analysis of the aircraft itself) and digital forensics. In particular, the physical and chemical forensics of the drone airframe must be considered to identify the drone operator, as identifying information for the drone operator is often not stored on the drone. In many cases, the pilots of drones found in no-fly zones have been identified using fingerprints found on the drones. In addition, soil, microscopic evidence, and gunpowder residue can also provide important information to identify the country of manufacture or origin of the drone. In South Korea, the fingerprints of all adults are registered, and in several cases involving unidentified drones, these fingerprints have been used to identify individuals. Such biometric evidence, such as fingerprints, is particularly suitable for identifying the pilot or for other investigative leads (see Fig. 4).
Fig. 3.
Drone forensics block diagram.
Fig. 4.
Drone forensics algorithm.
When it comes to digital forensics, live forensics must be taken into consideration. In general investigations, live digital forensics is not often used; however, in drone forensics, it is essential to verify real-time information through live forensics, if possible, such as the identification information of the aircraft in flight, flight information, and aircraft details. Additionally, depending on the distributed storage characteristics of drones, various related information can be stored on the drone aircraft, SD card, controller, smartphone (application), etc. Drone forensics should be reviewed for possible forensic and omissions according to this scheme. However, the order in which forensics is conducted, based on the characteristics of complex forensics, is also important. It is necessary to review the drone forensics algorithm in this regard.
3.3. Drone forensics algorithms
In many cases, forensics is often conducted in two completely separate areas: digital forensics and non-digital forensics. When digital devices, such as computers, are seized, digital evidence is collected, and when crime tools, such as firearms or knives, are identified, non-digital forensic evidence is analyzed. As you can see, drones have both digital and non-digital evidence characteristics, each of which can be valuable information. Therefore, the forensic algorithm for drones should be conducted in the following order: 1) live forensics, 2) non-digital forensics, 3) digital forensics, as shown in Fig. 3. If the forensic sequence is not executed correctly, important evidence from live forensics or non-digital forensics may be destroyed or not found. In certain circumstances, this order can be modified, but care must be taken to ensure that it does not impact the next forensic step, such as damaging digital evidence by using chemicals to collect non-digital forensic evidence, or compromising non-digital evidence, such as fingerprints or DNA, while collecting digital evidence. Therefore, these points must be considered when conducting drone forensics.
3.4. Review of key drone forensics technologies
3.4.1. Non-digital forensics
3.4.1.1. Aircraft inspection
It refers to techniques for forensic examination of the drone itself. Essentially, it involves verifying the drone's owner using fingerprints, DNA, and other microevidence, or examining the drone's components to determine the manufacturer and country of origin. Due to the nature of general drones, there is a possibility that fingerprints, DNA, and other microevidence may be left on the propeller or main battery; therefore, it is necessary to check for this. However, if the drone is manufactured by a person not registered in Korea, or if it uses gloves, verification may be difficult. In general, forensic techniques can be applied to plastics, magnesium or aluminum alloys, carbon, and other materials. In a recent experiment, DNA was detected about 32 % of the time by touching five surfaces of the drone and analyzing them for DNA. Additionally, microanalysis of the drone's surface may provide further information about the flight. It is also possible to estimate the country of manufacture based on the parts or materials used.
3.4.1.2. Environmental analysis techniques
It refers to a technique that analyzes the surrounding environment of a drone. By analyzing the crash environment, it is possible to estimate the direction of the drone's crash or its flight direction, as well as the speed and altitude at the time of the crash. Even if the actual drone is not recovered, it is possible to find evidence to trace the drone or pilot by analyzing the scene where the drone may have taken off or had a pilot. Video-based forensics [34], trajectory tracking techniques [35], and other forensic techniques used at traffic accident scenes or safety accident scenes can be used.
3.4.2. Digital forensics
3.4.2.1. Offline digital forensics
It is a technique for collecting and analyzing data from drones. The drone stores flight path, altitude, speed, azimuth, pitch, roll, and various sensor data, as well as system and airframe information, controller settings, control sensitivity, and event log status, among other details. Additionally, if the drone is filming, it stores information such as camera images, photos, and timestamps. These data can be key evidence in determining a drone's flight path, origin, and purpose, and it is essential to obtain them. This data can be analyzed using manufacturer programs such as DJI or Parrot, or by obtaining the original data through a dedicated forensic program. Manufacturer programs such as DJI Assistant are convenient to use, but they do not provide original data and are difficult to use if the connection port is broken. Also, depending on the manufacturer or type of drone, there may not be enough programs available. Legally, there is also the issue of whether the data provided by the manufacturer can be used as evidence in a court of law. Professional drone forensics programs are designed to analyze drone data professionally. In addition to checking basic flight data, sensor values, and shooting information, they can also perform advanced tasks, such as analyzing the cause of a drone crash through artificial intelligence analysis of the data.
If Drone use open code like PX4 or Ardupilot, the data structure is publicly available, and review sites are available to analyze it.
For aircraft that use private codes, such as DJI, you must use the manufacturer's program by default. However, the manufacturer's program does not provide the original data and does not include the entire flight data. Therefore, you can decrypt the encrypted data or bypass the encryption to obtain the original data. With the recent development of artificial intelligence technology, the technical basis for analyzing the causes of drone accidents based on flight data has been established, and various dedicated programs are being developed.
Fig. 3 illustrates a drone forensics program that analyzes a drone's flight data and estimates the cause of the crash using artificial intelligence. These programs demonstrate that it is possible to utilize and expand various applications using flight data, not just for checking flight data.
3.4.2.2. Live forensics
Live forensics refers to an investigation method that obtains forensically valid data about a system that is currently running [36]. Initially, live forensics was not widely accepted in many countries where traditional offline forensics was preferred. However, the need to obtain data that disappears when the system is turned off began to be emphasized [37] Especially in the case of recent cybercrimes, 90 % of malware resides in memory and hence its importance in detecting and analyzing cyber threats has been further emphasized [38]. In the case of drones, live forensics is recognized as a more important technology for drone accidents and crimes than in general, as data collected during flight is often more crucial than data collected after flight. Additionally, data from crashed drones is often destroyed or corrupted after the flight, and the drone aircraft is often not directly available. In this regard, related research is ongoing, such as studies to improve the efficiency of live forensics [20] and investigations into the methodology of open-source-based live forensic tools [39]. However, despite the advantages of live forensics, problems and difficulties of live forensics have been pointed out, such as difficulty in ensuring the integrity of data, difficulty in tracking evidence due to real-time changing logs, high technical barriers, and the possibility of data being altered or deleted [40].
3.5. Future development
3.5.1. Technical developments
Technologically, it is necessary to develop forensics specialized for drones. Currently, forensic technologies used for drones primarily utilize existing technologies and do not fully reflect the unique characteristics of drone technology. Therefore, it is necessary to develop technologies that automatically analyze drone flight data, analyze encrypted data, and Implement Chip-off technologies for drones. It is essential to secure live forensic technology that can be used as forensic evidence. As a result of destruction experiments on drones, even if the drone's connection port or PCB board is partially destroyed due to direct physical impact, it is likely to obtain complete information if the chip containing FC data is not destroyed.
In addition, for non-digital analysis, it is currently focused on fingerprints and DNA; however, it is necessary to consider developing additional evidence analysis techniques, such as extracting microevidence from the surface of the drone and developing forensic techniques based on the propulsion power (battery or internal combustion engine).
3.5.2. Legal developments
There may be various cases where drones are involved in terrorism, crimes, or accidents, and scenarios and response manuals are needed for each of these situations. In addition, when understanding the basic concepts and characteristics of forensics, the results of forensic investigations, such as live forensics, must be secured reliably. Therefore, evidence preservation procedures for general forensics and digital evidence preservation procedures should be considered simultaneously, and an investigation system that reflects these requirements should be developed. There are many cases where the jurisdiction of drones is ambiguous due to their wide range of activities and flight characteristics. Additionally, there are issues of authority, such as tracking and arresting drone pilots when they invade important facilities from a distance. In terms of the legal system, it will be crucial to clarify responsibilities and entities for neutralizing drones and implementing follow-up measures, as well as to develop legal procedures and standard treatment guidelines for drones.
4. Conclusions and policy recommendations
4.1. Research summary
Drone forensics is a key technology for responding to drone threats or problems such as drone terrorism, crime, and accidents. Unlike general forensics, drone forensics combines elements of digital forensics, physical and chemical forensics, and even in the case of digital forensics, live forensics is of great importance. Drone forensics should be conducted in light of the characteristics of these drones, and the order and overall system of forensics should be considered accordingly. Through the development of such a system and processing algorithms, legal and procedural issues related to securing evidence should be resolved, and at the same time, technical processing guidelines to enhance evidence should be organized.
4.2. Future research directions
There is a possibility that the scope of drone data can be further expanded, such as analyzing the causes of accidents or crashes through AI learning based on drone flight data. In the future, it is expected that various AI learning models can be compared, allowing for more accurate and rapid inferences based on such learning data. These data may also be used for analyses beyond accident causes and for learning purposes.
CRediT authorship contribution statement
Dongkyu Lee: Conceptualization. Wook Kang: Conceptualization, Methodology, Writing – review & editing.
Declaration of competing interest
The authors declare the following financial interests/personal relationships, which may be considered as potential competing interests:Dongkyu Lee & Wook Kang reports that the article publishing charges were provided by the Korea Aerospace Administration. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
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