Generation and analysis of tactics for anti-torpedo defense system

Bharati, P. Vijaya; Rao, S. Koteswara; Krishna, A. Rama

doi:10.1109/cict.2013.6558125

Cited by 6 publications

(2 citation statements)

References 2 publications

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“…After the launch of the jammer, the defense platform maintains a uniform and straight course. After the jammer enters the water and starts to work, the ship must choose the optimal course and speed to maneuver to avoid the incoming torpedo [13]. Figure 2 shows the evasion strategy of the defense platform, setting the torpedo to cut off the guide wire at T 1 and turn to acoustic homing.…”

Section: Defense Platform Maneuver Evasion Strategymentioning

confidence: 99%

Optimal Underwater Acoustic Warfare Strategy Based on a Three-Layer GA-BP Neural Network

Wang

et al. 2022

Sensors

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A defense platform is usually based on two methods to make underwater acoustic warfare strategy decisions. One is through Monte-Carlo method online simulation, which is slow. The other is by typical empirical (database) and typical back-propagation (BP) neural network algorithms based on genetic algorithm (GA) optimization, which is less accurate and less robust. Therefore, this paper proposes a method to build an optimal underwater acoustic warfare feedback system using a three-layer GA-BP neural network and dropout processing of the neural network to prevent overfitting, so that the three-layer GA-BP neural network has adequate memory capability while still having suitable generalization capability. This method improves the accuracy and stability of the defense platform in making underwater acoustic warfare strategy decisions, thus increasing the survival probability of the defense platform in the face of incoming torpedoes. This paper uses the optimal underwater acoustic warfare strategies corresponding to incoming torpedoes with different postures as the sample set. Additionally, it uses a three-layer GA-BP neural network with an overfitting treatment for training. The prediction results have less error than the typical single-layer GA-BP neural network, and the survival probability of the defense platform improves by 6.15%. This defense platform underwater acoustic warfare strategy prediction method addresses the impact on the survival probability of the defense platform due to the decision speed and accuracy.

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Section: Defense Platform Maneuver Evasion Strategymentioning

confidence: 99%

Optimal Underwater Acoustic Warfare Strategy Based on a Three-Layer GA-BP Neural Network

Wang

et al. 2022

Sensors

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“…Threat analysis is another important requirement of a TDS. Threat analysis system assesses all possible threats in the vicinity and it assigns a threat priority level for all the targets [11]. The system will recommend a course to steer, as well as a countermeasure deployment to maximise escape probability.…”

Section: System Of Systems Architecture For Generic Torpedo Defencementioning

confidence: 99%

System of Systems Architecture for Generic Torpedo Defence System for Surface Ships

Jomon¹,

Jojish²,

Santhanakrishnan³

2019

AiMT

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Protecting war ships from torpedo attack is considered as the most challenging task in Anti-Submarine Warfare. Torpedo Defence System (TDS) is an essential fitment on modern high value platforms. Timely detection and identification of a torpedo attack is the primary function of a TDS. Localisation and countermeasures against the weapon are the next stage in torpedo defence. Detection of modern torpedoes with long endurance can only be achieved using an underwater sensor suit with wide frequency coverage. Tactical use of multiple counter measures is essential for evading an attacking torpedo with intelligent homing mechanism. Individual sensors and counter measures are no longer considered as a solution; they are rather considered as components of a large network of systems to protect the platform from torpedo attack. A System of Systems (SOS) architecture with multiple sensors, processing techniques, countermeasures and tactics are presented in this paper for achieving fail-safe torpedo defence capability.

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A Communication Method between High-speed UUV and Distributed Intelligent Nodes

Wang

et al. 2019

Mobile Netw Appl

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Generation and analysis of tactics for anti-torpedo defense system

Cited by 6 publications

References 2 publications

Optimal Underwater Acoustic Warfare Strategy Based on a Three-Layer GA-BP Neural Network

Optimal Underwater Acoustic Warfare Strategy Based on a Three-Layer GA-BP Neural Network

System of Systems Architecture for Generic Torpedo Defence System for Surface Ships

A Communication Method between High-speed UUV and Distributed Intelligent Nodes

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