Defence Science Journal
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Elliptical Multi Orbital Truncated Flexible Patch Antenna Using PDMS Substrate for Sub 6 GHz Applications
Full text linkThis paper presents an elliptical-shaped multi-orbital truncated patch antenna applicable forsub-6 GHz bands. The sub-6 GHz bands cover 5.8 GHz high-speed wireless communication. The antenna is designed on a Poly Dimethylsiloxane (PDMS) substrate. PDMS is used for designing the proposed antenna. It is a flexible substrate with a dielectric constant εr value of 2.7 and a loss tangent tan δ value of 0.022. The substrate dimension is 20×15×1.6 mm3in which a patch is created with the size of 12.5×13 mm2. The proposed antenna resonates at 6.2 GHz showing a reflection coefficient (s11) value of -37 dB. The impedance bandwidth of the antenna is 1.225 GHz in the range of 5.5-6.725 GHz frequency, and the maximum peak gain is about 3.5 dB. The proposed antenna is simulated, fabricated, and experimentally tested
A Drone Based Image Dataset Generation Methodology for Single Image Super Resolution
Full text linkThe advancements in drone technologies, digital imaging, computer vision techniques, and the liberalized laws related to drone flying have opened up drone-based applications such as the delivery of supplies, search and rescue, aerial surveillance, and so on. The drones, especially the nano/micro/small drones, may be mounted with only low-resolution camera(s) due to their maximum takeoff weight limitations. The low-resolution images generated by the cameras, if used for landing, can result in faulty detection unless the photos are taken from a very close distance to the point of interest. Detection and recognition of the point(s) of interest as early as possible is required to ensure sufficient response time for safe maneuvering. Hence, the images are to be captured at greater heights or distances from the point(s) of interest, and obtaining the high-resolution images from the captured low-resolution images is crucial. The High Resolution (HR) and the Low Resolution (LR) image pairs for training super-resolution models in the works presented in literature are generated using two different cameras or the HR images are captured by the camera and LR images are generated by degrading the HR images. As both methods are not appropriate for small/micro/nano category drones, we propose a novel method based on Ground Sampling Distance (GSD) to capture the LR and HR images. In this paper, we have presented the designed methodology for the creation of a dataset using drone-mounted cameras covering a broad spectrum of views of the target(s) suitable for training and testing of the Single Image Super-Resolution (SISR) models. We also present a methodology for selecting an appropriate target for imaging that enables the visual quality assessment of the developed super-resolution model
A C4 Software for Anti Drone System
Full text linkMini unmanned aerial vehicles (UAVs), commonly known as small drones, have seen outstanding advancements in recent years and have been used in a variety of fields. However, their potential misuse for illegal activities and the risks they pose to safety and privacy have raised concerns. To address these issues, we propose a Command, Control, Communications, and Computers (C4) software able to manage and control anti-drone systems. Our software solution includes an easy-to-use dashboard that processes and displays video data from surveillance sensors. It incorporates AI-powered functionalities, including object detection, target tracking, and classification of small drones. At the inference stage, the network models for drone detection and classification functionalities have achieved an accuracy exceeding 96 %. We have evaluated the effectiveness of our solution by deploying it in a no-fly zone, where it successfully identified and tracked drones in near real-time. The proposed control system provides unified information with which the entire anti-drone process can be managed starting from the detection of each threat
An Experimental Study of Odometer as a Navigation aid for Land Vehicle Application
Full text linkStrap-down inertial navigation system (SINS) shall provide position, velocity, and orientation information with reference to a pre-defined reference frame. The SINS shall have excellent accuracy over a short duration and is highly self-contained. However, the errors in navigation solutions build up exponentially with time and make the system output very unstable. In order to mitigate these errors, there is a need for a damping mechanism through external aiding sensors. In this article, one such approach is proposed to improve navigation accuracy for land vehicles in the GNSS (Global Navigation Satellite Systems) denied environment. The design and implementation of an odometer are carried out with the use of inductive proximity sensors and a mounting assembly to attach the odometer to one of the non-steering wheels of a vehicle. The odometer gives the pulse-high and pulse-low output with reference to the rotation of the wheel to which it is attached. Vehicle ground velocity is derived through sensed output pulses processed through quadrature decoder circuitry. Odometer measurements along with non-holonomic constraints (NHC) are used for minimizing velocity and position errors in SINS using an extended Kalman Filter (EKF) technique. Field trials are carried out to validate the proposed scheme of hybrid navigation with odometer design and experimental results are presented with a positioning accuracy of 0.05 % of distance travelled (DT)
Urban Operation Threat Assessment after a Multistage Radiological Dispersive Device Attack
Full text linkThe urban environment may be a relevant setting for special military operations. Due to the options offered by urban infrastructure, this environment can be an essential catalyst for the proliferation of local asymmetric actions. These actions are triggered by extremist groups offering resistance to regular troops. Improvised weapons such as radiological dispersive devices (RDD) can be used to provoke even more threatening situations by increasing the risks of operations. This study is directed, via computer simulation using the Hot Spot Health Physics code, to a hypothetical context where a multistage RDD (RDD-M) is triggered in two non-simultaneous phases. This non-linear triggering causes overlapping contamination and impacts the coping strategy and the projections of variations in the size of the potentially affected population. In this study, the primary consideration is the contamination carried out at such a level that the association between human exposure and deterministic effects is feasible. The exposure to high doses of radiation at short distances about the triggering location of the device. The simulated data show that the threats are leveraged, and the environmental variables have a high value when assessing the criticality of the situation and establishing effective countermeasures
Performance Evaluation of DGNSS Receiver for Dynamic Military Applications
Full text linkIn military applications, a highly accurate and precise navigation system is necessary for some ground-based combat system applications to navigate the vehicle and mark the location of the fuses and pickets laid by the mobile equipment. Few companies across the globe have developed expertise in manufacturing Global Navigation Satellite System (GNSS) receivers with Real Time Kinematics (RTK) capability along with integrated INS. On mobile equipment, it is not always possible to precisely place the Differential GNSS (DGNSS) antenna and GNSS receiver at the point for which the data needs to be marked. For such applications, lever arm calculation needs to be implemented. Also, due to uneven terrain conditions and slopes, the vehicle undulates up to 10o about its longitudinal and transverse axis. This dynamic condition induces considerable errors in the actual data. During the fuse laying process, there is also a continuous requirement for real-time location data in the GNSS-denied environment for a short period. INS was integrated with the GNSS receiver. We discuss test methodology for GNSS receiver performance evaluation. Experimentations were performed, taking into consideration these requirements. Data collected are also analyzed and discussed. Test results confirmed that the module is accurate with an accuracy of a few centimeters
An Efficient Spoofing Attack Detection Using Deep Learning Based Physical Layer Security Technique
Full text linkSpoofing attack detection plays a crucial role in the defence field, involving critical and highly secured data processing. The accurate attack detection mechanism prevents unauthorised access to sensitive information, thereby protecting National security. Physical Layer Security (PLS) is a promising emerging technique that uses the wireless channel’s randomness to secure the communication network. The spoofing attack is one of the severe threats to the wireless network, where the attacker imitates the legitimate user to launch an attack against the network. This paper investigates the channel characteristics-based physical layer technique to detect spoofing attacks. For static radio environments, the two-sample independent hypothesis testing is used to identify the spoofing attack, showing an improvement in detection accuracy of 97 %. The attack detection problem is considered a Reinforcement Learning (RL) based classification problem for a challenging dynamic radio environment. It is simulated using the actor-critic-based Deep Reinforcement Learning (DRL) technique with the help of the Reformed Deep Deterministic Policy Gradient (Re-DDPG) algorithm. The simulated results show that the proposed method performs better than the existing strategies and achieves a Receiver Operating Characteristics (ROC) value of 0.96. The detection accuracy of the proposed method can reach up to 98 %, with precision and recall of about 98 % and 99 %, respectively.
 
Characterization and Modelling of Particulate Composite with Flaky Aluminium Additives
No full textThe utilisation of flaky aluminium as an additive in the composite matrix has shown the ability to overcome the brittle nature encountered in epoxy resins. The additive increases the overall composite toughness without compromising its strength. The novelty of the present work is the demonstration of modelling the constitutive response of the particulate composite from the uniaxial tension tests conducted at three different displacement rates. Utilising two different mean-field homogenisation schemes (Dilute inclusion and Mori-Tanaka), the macro-scale properties were estimated and compared with the material constants obtained from experiments for this new particulate composite, which is proposed in the current study. The rate-independent response, at lower loading rates, is modelled by the elasto-plastic (EP) model, and the rate-dependent response, at higher loading rates, is modelled by elastic-viscoplastic (VP) model while capturing an inelastic deformation as seen in the fractographs. The EP and VP model material constants are then successfully obtained by optimisation employing the Levenberg–Marquardt algorithm and are eventually used in validating the experimental stress response
Selected Papers from 4th National Aerospace Propulsion Conference NAPC 2022
Full text linkThe National Aerospace Propulsion Conference (NAPC) is a national conference dedicated to aerospace propulsion technologies. Two erstwhile popular conference series, the National Propulsion Conference (NPC) and the National Conference on Air-Breathing Engines (NCABE) were merged to result in NAPC. This biennial conference is intended to bring together the entire propulsion community spanning the industry, academia and the research labs nationwide. The aerospace propulsion-centred conference is considered an ideal opportunity to showcase one’s research activities with peers and foster future collaborations through networking. The 4th edition of the conference, NAPC-2022, comprised a keynote lecture, several topical invited lectures and presentations of contributed papers in parallel sessions. This special issue contains eight manuscripts selected based on peer-reviews of selected papers presented during the conference. The manuscripts broadly cover several aspects pertaining to aerospace propulsion that includes airbreathing engine components such as intakes, compressors, combustors and nozzles. From the rocket propulsion (non-airbreathing), there are papers that investigate the rocket motor grain port alignment and another paper on the heat transfer characteristics of a supersonic rocket nozzle
Military Decision Support with Actor and Critic Reinforcement Learning Agents
Full text linkWhile the recent advanced military operational concept requires an intelligent support of command and control, Reinforcement Learning (RL) has not been actively studied in the military domain. This study points out the limitations of RL for military applications from literature review and aims at improving the understanding of RL for military decision support under the limitations. Most of all, the black box characteristic of Deep RL makes the internal process difficult to understand in addition to complex simulation tools. A scalable weapon selection RL framework is built which can be solved either by a tabular form or a neural network form. The transition of the Deep Q-Network (DQN) solution to the tabular form makes it easier to compare the result to the Q-learning solution. Furthermore, rather than using one or two RL models selectively as before, RL models are divided as an actor and a critic, and systematically compared. A random agent, Q-learning and DQN agents as a critic, a Policy Gradient (PG) agent as an actor, Trust Region Policy Optimization (TRPO) and Proximal Policy Optimization (PPO) agents as an actor-critic approach are designed, trained, and tested. The performance results show that the trained DQN and PPO agents are the best decision supporter candidates for the weapon selection RL framework