Torpedo performance Markov model. Issue 23 (15th December 2015)

• Record Type: Journal Article
• Authors: Hui, Lin; Wang, Kuei Min
• Is Part Of: Expert systems with applications. Volume 42:Issue 23(2015)
• Page Start: 9129
• Page End: 9136
• Publication Date: 2015-12-15
• Subjects: Behavior -- CM -- Markov chain -- Submarine -- Torpedo -- TPMM; Expert systems (Computer science) -- Periodicals; Systèmes experts (Informatique) -- Périodiques; Electronic journals; 006.33
• DOI: 10.1016/j.eswa.2015.07.077
• Languages: English
• ISSNs: 0957-4174

Abstract

Highlights: Optimal number of CM vs. a torpedo attack is two-pairs of jammers and two decoys. Torpedo performance decreases exponentially as the countermeasure number increases. Markov theory is useful in analyzing interactions between submarines and torpedoes. Abstract: The improved evasive capability of the modern deiseal submarine can downgrade the performance of a torpedo seriously. However, a few studies have concerned the sophisticate diesel submarine as a main factor for the influence of a torpedo's attack. This paper presents a torpedo performance Markov model for making quick analyses on a torpedo performance in pursuit of a diesel submarine under various conditions. This model takes into account the effectiveness of submarine's counter measures and maneuvering behaviors of both sides. The Markov process is used and six states are sorted out for representing the dynamic behaviors for both of submarine and torpedo systematically. Through cases analyses, we prove that the torpedo performance is deteriorating exponentially as the number of counter measure is increasing. This analytical result may refine the anti-submarine warfare decision to avoid the possible misleading by solely relying on the deterministic torpedo probability of kill in the engagement. It also identifies that two pairs of jammer coupling with two decoys can be the best combination to saturate torpedo attack that can direct provide the decision makers a basic doctrine for controlling their engagement behaviors.