Introduction to Electronic Warfare Modeling and Simulation

Adamy,

doi:10.1049/sbra011e

Cited by 60 publications

(49 citation statements)

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“…We adopt the scanning and tracking modes: the circular scanning mode that monit detect a target and the conical scanning mode that keeps tracking the target when the in the circular scanning mode [14]. …”

Section: Scanning and Tracking Modesmentioning

confidence: 99%

Simulation of Dynamic EADs Jamming Performance against Tracking Radar in Presence of Airborne Platform

Rim¹,

Jung²,

Koh³

et al. 2015

International Journal of Aeronautical and Space Sciences

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We propose a numerical scheme to simulate the time-domain echo signals at tracking radar for a realistic scenario where an EAD (expendable active decoy) and an airborne target are both in dynamic states. On various scenarios where the target takes different maneuvers, the trajectories of the EAD ejected from the target are accurately calculated by solving 6-DOF (Degreeof-Freedom) equations of the motion for the EAD. At each sampling time of the echo signal, the locations of the EAD and the target are assumed to be fixed. Thus, the echo power from the EAD can be simply calculated by using the Friis transmission formula. The returned power from the target can be computed based on the pre-calculated scattering matrix of the target. In this paper, an IPO (iterative physical optics) method is used to construct the scattering matrix database of the target. The sinc function-interpolation formulation (sampling theorem) is applied to compute the scattering at any incidence angle from the database. A simulator is developed based on the proposed scheme to estimate the echo signals, which can consider the movement of the airborne target and EAD, also the scattering of the target and the RF specifications of the EAD. For applications, we consider the detection probability of the target in the presence of the EAD based on Monte Carlo simulation.

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Section: Scanning and Tracking Modesmentioning

confidence: 99%

Simulation of Dynamic EADs Jamming Performance against Tracking Radar in Presence of Airborne Platform

Rim¹,

Jung²,

Koh³

et al. 2015

International Journal of Aeronautical and Space Sciences

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“…The results of the simulations are shown in Table 4. In addition to the traffic simulation we have also defined four different simulations in the Electronic Warfare (EW) domain (Adamy and David, 2006). Each simulation has been separately defined and executed.…”

Section: Deployment Model Generation Performancementioning

confidence: 99%

S-IDE: A tool framework for optimizing deployment architecture of High Level Architecture based simulation systems

Çelik

Tekinerdoğan

2013

Journal of Systems and Software

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One of the important problems in High Level Architecture (HLA) based distributed simulation systems is the allocation of the different simulation modules to the available physical resources. Usually, the deployment of the simulation modules to the physical resources can be done in many different ways, and each deployment alternative will have a different impact on the performance. Although different algorithmic solutions have been provided to optimize the allocation with respect to the performance, the problem has not been explicitly tackled from an architecture design perspective. Moreover, for optimizing the deployment of the simulation system, tool support is largely missing. In this paper we propose a method for automatically deriving deployment alternatives for HLA based distributed simulation systems. The method extends the IEEE Recommended Practice for High Level Architecture Federation Development and Execution Process by providing an approach for optimizing the allocation at the design level. The method is realized by the tool framework, S-IDE (Simulation-IDE) that we have developed to provide an integrated development environment for deriving a feasible deployment alternative based on the simulation system and the available physical resources at the design phase. The method and the tool support have been validated using a case study for the development of a traffic simulation system.

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“…EW is defined as the art and science of preserving the use of the electromagnetic spectrum for friendly use while denying its use to the enemy [1,2].…”

Section: ⅰ Introductionmentioning

confidence: 99%

GPS Anti-Jamming Using Beamforming Technique

Choi¹

2016

Journal of the Korea Institute of Information and Communication

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Because GPS signals are weak, system jamming is a real and present danger. This can happen when the receiver is subjected to intentional or unintentional interference by a transmitter. If the jamming signal is strong enough, the receiver can be operated to take corrective action automatically. Current methods to protect GPS receiver from jamming condition are based on spatial filtering. In this paper, the beamforming as referred to in signal processing technique used in arrays for directional signal reception was suggested and analyzed for anti-jamming. In order to change the directionality of the array when receiving a jamming signal, a beamformer can control the signal at each sensor. Therefore, cutoff angle θ was measured in the opposite direction of the jammer. GPS signals are only processed when the antenna element is within inside the cutoff angle. As a result, GPS positioning can be used in condition under cutoff angle 30°.키워드 : 위성항법, 재밍 신호, 공간 필터링, 빔포밍, 재밍 대응

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Introduction to Electronic Warfare Modeling and Simulation

Cited by 60 publications

References 0 publications

Simulation of Dynamic EADs Jamming Performance against Tracking Radar in Presence of Airborne Platform

Simulation of Dynamic EADs Jamming Performance against Tracking Radar in Presence of Airborne Platform

S-IDE: A tool framework for optimizing deployment architecture of High Level Architecture based simulation systems

GPS Anti-Jamming Using Beamforming Technique

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