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Optimizing Probability of Intercept Using XCS Algorithm

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Innovations in Bio-Inspired Computing and Applications (IBICA 2018)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 939))

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Abstract

In battle scenarios, the amount of RF signals/energy intercepted by a sensor like Radar Warning Receiver is characterized by a metric called Probability of Intercept. Due to increase in density and complexity of radars, achieving optimal POI within given cost-constraints is challenging. The basic problem arises since radars scan in spatial (and hence time domain), whereas RWR scan in frequency domain. Synchronizing RWR’s reception frequency with same of Radar and, at the time when radar is illuminating Aircraft will require more than analytical techniques. Situation becomes more complicated with multiple radars and radars with Low Probability Intercept (LPI) signatures. In this paper, we explore how to exploit eXtended Classifier System (or XCS) to tackle this problem.

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Correspondence to Ravindra V. Joshi .

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Joshi, R.V., Chandrashekhar, N. (2019). Optimizing Probability of Intercept Using XCS Algorithm. In: Abraham, A., Gandhi, N., Pant, M. (eds) Innovations in Bio-Inspired Computing and Applications. IBICA 2018. Advances in Intelligent Systems and Computing, vol 939. Springer, Cham. https://doi.org/10.1007/978-3-030-16681-6_33

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