Paper
29 May 2013 Determining the flare dispensing program effectiveness against conical-scan and spin-scan reticle systems via Gaussian mixture models
Author Affiliations +
Abstract
The reticle systems which are considered as the classical approach for determining the angular position of radiating targets in infrared band are widely used in early generation surface-to-air and air-to-air infrared guided missile seekers. One of the cost-effective ways of protecting aircrafts against these missiles is to dispense flare decoys from the countermeasure dispensing system (CMDS) integrated into the aircraft platform. Although this counter-measuring technique seems very simple, if not optimized carefully, it may not be effective for protecting the aircraft. Flares should be dispensed in accordance with a specific dispensing program which determines the number of flares to be dispensed from each dispenser of the CMDS and timing sequence of dispensing. Optimizing the parameters of the dispensing program is not trivial. It requires a good understanding of the operating principle of the threat seeker, operational capabilities of own platform and engagement scenario between them. In the present paper, we propose a complete simulation-based procedure to form an effectiveness boundary of flare dispensing programs against the spin-scan and conical-scan reticle seekers. The region of effectiveness is determined via Gaussian mixture models. The raw data is collected via extensive number of simulations using a MATLAB-coded simulator which models reticle-based seeker, aircraft radiation, aircraft motion, aircraft CMDS system, flare motion and flare radiation.
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Mehmet Cihan Şahingil and Murat Şamil Aslan "Determining the flare dispensing program effectiveness against conical-scan and spin-scan reticle systems via Gaussian mixture models", Proc. SPIE 8752, Modeling and Simulation for Defense Systems and Applications VIII, 87520H (29 May 2013); https://doi.org/10.1117/12.2015723
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KEYWORDS
Reticles

Missiles

Signal processing

Modulation

Expectation maximization algorithms

Target designation

Mirrors

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