In the proposed paper, we analyzed the attenuation by atmospheric factors in the frequency bands for Radar. Radio frequencies using radar systems is susceptible to attenuation by atmospheric factors. The proposed paper analyze the attenuation by atmospheric factors in L, S, C and X bands. Among the attenuation of signals by atmospheric factors, the attenuation by water vapor and oxygen, which is atmospheric attenuation compared to the detection range, is at least 0.416 dB in the L band and 2.6 dB in the X band. The attenuation by rainfall is at least 0.06 dB in the L band and 20.2 dB in the X band. Finally, the attenuation by atmospheric factors is at least 0.416 dB in the L band and 22.8 dB in the X band. In conclusion, it is judged that the attenuation of atmospheric and rainfall is minimal in the L, S, and C bands, and that the influence of attenuation is large in the X band.

Infrared imaging is a powerful non-destructive and non-invasive technique to detect infrared radiations and capture valuable insights inaccessible through the visible spectrum. It has been widely used in the military for reconnaissance, hazard detection, night vision, guidance systems, and countermeasures. There is a huge potential for machine learning models to improve trivial infrared imaging tasks in military applications. One major roadblock is the scarcity and control over infrared imaging datasets related to military applications. One possible solution is to use synthetic infrared images to train machine learning networks. However, synthetic IR images present a domain gap and produce weak learning models that do not generalize well. We investigate adversarial networks and Explainable AI(XAI) techniques to refine synthetic infrared imaging data, enhance their realism, and synthesize refiner networks with XAI. We use a U-Net-based refiner network to refine synthetic infrared data and a PatchGAN discriminator to distinguish between the refined and real IR images. Grad-CAM XAI technique is used for network synthesis. We also analyzed the frequency domain patterns and power spectra of real and synthetic infrared images to find key attributes to distinguish real from synthetic. We tested our refined images on the realism benchmarks using frequency domain analysis.

Landing a helicopter on a moving ship requires accounting for the ship's attitude. However, it is not only challenging to visually assess the ship's attitude, but it also creates illusions for the pilot, increasing the risk of accidents. In this study, we propose an image-based ship attitude estimation method to assist helicopter landings. The proposed method enhances landing safety by predicting the ship's heave, pitch, and roll using only helicopter-mounted optical devices and pre-trained deep learning models, without requiring communication with the ship. To implement this approach, we generated a dataset by simulating a virtual sea environment and ship motion. Using this data, we trained deep learning models to predict the ship's attitude based solely on images. Experimental results confirm the feasibility of the proposed method, with VGG-16 demonstrating particularly effective attitude prediction under simulated conditions.

Effective border security is crucial in managing and mitigating firearm-related threats. While prior research has focused on firearm detection, it lacks contextual analysis. This paper advances firearm-related incident assessment by integrating pose estimation to improve gun violence detection. Our novel approach extracts body and firearm pose graphs and employs Graph Attention Networks(GAT) for graph analysis to accurately identify gun violence incidents. By recognizing associated actions, our system provides greater situational awareness beyond mere firearm detection. Utilizing Graph-LSTM, we capture spatial and temporal information. As a result, our proposed algorithm is lighter and more accurate than the CNN-LSTM model used as a baseline, achieving test F1-scores of 82.04 % on our collected data.

This paper studies the implementation of an airborne AESA radar Hardware-in-the-Loop Simulation(HILS) based on near-field beam focusing. A RF simulated signal generator based on Digital RF memory receives a Tx signal from an exciter receiver processor unit of AESA radar, and then it transmits simulated various targets, clutter, and jamming signal through 400 phase array antennas. At that time, the airborne AESA radar focuses Rx beam in near-field region of an anechoic chamber in order to simulate a far-field beam pattern, and receives these signals from 1.5 m away. Through the simulated airborne radar environment inside an anechoic chamber, it reduces the number of flight tests and performs tests on the ground excluding external environmental factors.

Video bit-rate control techniques are essential for efficiently transmitting videos over communication networks. These techniques have been pivotal in broadcasting and internet streaming services, and they could significantly enhance defense capabilities if applied to defense and aerospace imaging systems. Therefore, this paper first reviews the history and standard technologies of video coding, then describes the standard trends of the latest video coding technologies. Finally, it outlines the features of the latest video bit-rate control techniques and discusses their applicability in the defense and aerospace fields.

For weight reduction we have applied Ti-6Al-4V, a lightweight and high-strength material, to a high-pressure gas cylinder for rapid cooling airborne electro-optical/infrared sensors. We have designed, manufactured using electron beam welding, and evaluated various performance(e.g., proof pressure tests, cooling tests). As results, a weight reduction of approximately 29 % was achieved compared to the previous gas cylinder made of STS630. Additionally, representative micro-structures that improve mechanical properties, such as acicular α' phase Martensite and Widmanstatten structure, were observed in the fusion zone. Furthermore, the cooling performance was successfully met under even high-temperature conditions.

In this study, flight tests were conducted to measure vibrations transferred from the helicopter's bomb rack to the external store. Hovering, S-turns, accelerating, decelerating, ascending, descending, and straight flight were performed according to the flight envelope. Vibration data was measured with 3-axial accelerometers mounted on the external store and converted into PSD(Power Spectral Density) using commercial data software. To identify the vibration level, G_RMS values were calculated for all flight conditions. The results confirmed that the measured vibration levels were significantly lower than the MIL-STD-810G vibration profile. Finally, a new vibration test specification was proposed using the VRS(Vibration Response Spectrum) method, which is expected to aid in the development of an optimized design for the external store.

Testing and evaluation is essential for the modification and installation DIRCM onto an aircraft. DIRCM is an optical device that deceives infrared guided missiles. There are many things to consider when installing DIRCM on an aircraft and operating it. In order to verify the function and performance of DIRCM, the characteristics of the linkage equipment were presented, and the expected flight sortie was proposed by specifying the test and evaluation methods, items, and detailed test conditions.

Entering the 1990s, 80 to 90 % of aircraft losses occurred due to MANPADS(Man Portable Air Defense System) attacks, and during the Russian invasion of Ukraine, Ukraine used MANPADS, a type of infrared guided missile, to kill many aircraft. The importance of survival systems is increasing as aircraft are intercepted. In this paper, we present a test equipment development plan to verify that EWC, which acts as an MC of a survival system, responds optimally in real time without delay in a situation simulating an actual threat. The EWC test equipment presented in this paper not only includes functions such as interface verification and self-diagnosis, but also includes automatic EWC functional performance testing and operation scenario-based EWC logic verification functions to verify that the EWC responds optimally in real time in various threat cases.

As the modern warfare continuously evolves into one that is network-centric, the amount of data a weapon system has to handle is rapidly growing, which applies not just to the internal data processing software but also to the UI software. Not only is the amount of data growing, but also is the complexity of handling such data, which when combined together creates a significant delay in updating relevant components in a UI software. In the context of the defense industry, split-second delay in visual component update can lead to catastrophic failure in making strategic decisions. This paper presents a novel method that utilizes asynchronous functions to control the program flow and reduce the delay in updating multiple visual components of a modular software. We apply this method to our modular UI software which uses MVVM pattern, where we were able to reduce the delay by an average of 78.4 %.

This paper simulates an environment similar to the operational environment of intelligent remote control smart landmines on the battlefield and describes a method for configuring a wireless personal area network in which the control unit(Master node) wirelessly controls smart landmines(Slave nodes) and manages the separation of slave nodes from the master node. We propose a study on a method of grouping by direction using the characteristics of directional antennas without a location tracking device(e.g., GPS). The short-distance wireless network communication environment, within a maximum range of 100 meters, is designed based on the IEEE 802.15.4e standard. The signal strength of the slave nodes is collected using the directional antennas attached to the master node, and the signal strength is measured by direction(0 degrees, 90 degrees, 180 degrees, 270 degrees). The process of specifying and controlling groups by direction is described. The effects of the proposed research show improvements such as reducing the production cost of smart landmines(slave nodes) with one-time use characteristics and simplifying the overall system.

The Concept Model of Mission Space(CMMS) can be regarded as an ontology that systematically represents knowledge within a military domain. Ensuring the consistency of this ontology is crucial, and its consistency must be verifiable. This paper presents a case study on the consistency verification of the Korean CMMS, referred to as CMMS-K. The verification feature can detect inconsistencies such as duplication, missing links, and circular definitions within the ontology elements. This capability is achieved through the formality of the Methontology template, which provides a structured specification of ontology elements. The implemented feature demonstrates the practical ability to perform verification and highlights the future prospects of the Korean CMMS.

The emergence of MUCS(Manned-Unmanned Complex System), incorporating numerous robots surpassing human's control capabilities, is inevitable on future battlefields and necessitates revolutionary robot operation technology. Since MUCS should be structured over the current command and control networks in Korean military binding its constituent elements ranging from small echelons to joint forces, various types of MUCS configurations and manned-unmanned teaming(MUM-T) types are also defined. Then a methodology for robot collaboration with aiming at real-time situation response is proposed. The method is basing on the situational response decision-making model in order to operate multiple robots cooperatively in respond to serial events occurring in real-time using the concept of control measure which is the origin/object triggering a task. In addition, a set of decision-making rules is devised and compared to decisions optimized by the model. Through illustrative experiments the suggested method is checked to be viable for realizing MUM-T and operating multiple robots in MUCSs.

User complaints are occurring due to the inability to meet user needs, such as the performance and ease of use of military supplies. Over the past five years, an average of 1,115 user complaints have occurred, and the Defense Agency for Technology and Quality(DTaQ) is handling the complaints collected from the requesting military. This user complaint information is accumulated as unstructured data in the Quality Information Service(IQIS) and Excel, making systematic analysis difficult. Therefore, this study aims to identify the status of user complaints related to air weapon systems using network analysis. This research is significant as it quantitatively analyzes user complaint data through the analysis of unstructured data, and the results are expected to serve as reference material for future quality assurance activities and user complaint handling.

Bacillus anthracis, a potential biological agent for terrorism, has been actively investigated for its underlying property and phylogenetic origin in the field of Microbial forensics. With the advancement of next generation sequencing(NGS) technology, in silico analysis becomes feasible at the whole genome sequence level, reducing the time and cost. In this paper, we suggested a methodology for identifying unknown samples form the field, which simulate real forensic evidence rather than highly purified samples, utilizing two in silico methods: k-mer analysis and whole genome single-nucleotide polymorphism(wgSNP). We performed prefix-based k-mer analysis using 964 NGS raw data obtained form the NCBI database, along with the NGS data from the unknown samples, by mapping the reads to Ames Ancestor and obtaining the consensus sequence. When analyzed together with 844 assembled sequences obtained form the NCBI database, it was determined that the unknown samples belong to the Injectional anthrax group, which was an infectious group identified among heroin users in Norway in 2000. wgSNP analysis has categorized the sample into discrete low-SNP group-I and high-SNP group-II, with a difference of up to 9 SNPs within each group. We observed 30 SNP positions in group-I, which includes the unknown samples, and confirmed that the SNP of A4564 was identical to that of the unknown samples. These results demonstrate that prefix-based k-mer, and wgSNP analysis can be effectively used for the collection of microbial forensic evidence from field samples.