• Journal of Ocean Engineering and Technology
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• v.20 no.1 s.68
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• pp.69-76
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• 2006

The design of efficient search path to maximize the Cumulative Detection Probability(CDP) is mainly dependent on experience and intuition when searcher detect the target using SONAR in the ocean. Recently with the advance of modeling and simulation method, it has been possible to access the optimization problems more systematically. In this paper, a method for the optimal search path calculation is developed based on the combination of the genetic algorithm and the calculation algorithm for detection range. We consider the discrete system for search path, space, and time, and use the movement direction of the SONAR for the gene of the genetic algorithm. The developed algorithm, OASPP(Optimal Acoustic Search Path Planning), is shown to be effective, via a simulation, finding the optimal search path for the case when the intuitive solution exists. Also, OASPP is compared with other algorithms for the measure of efficiency to maximize CDP.

• Journal of the Korea Institute of Military Science and Technology
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• v.15 no.3
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• pp.272-287
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• 2012

The optimal use of sonar systems for detection is a practical problem in a given ocean environment. In order to quantify the mission achievability in general, measure of effectiveness(MOE) is defined for specific missions. In this paper, using the specific MOE for detection, which is represented as cumulative detection probability(CDP), an integrated software package named as Optimal Acoustic Search Path Planning(OASPP) is developed. For a given ocean environment and sonar systems, the discrete observations for detection probability(PD) are used to calculate CDP incorporating sonar and environmental parameters. Also, counter-detection probability is considered for vulnerability analysis for a given scenario. Through modeling and simulation for a simple case for which an intuitive solution is known, the developed code is verified.

• Journal of the Korea Institute of Military Science and Technology
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• v.15 no.5
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• pp.601-614
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• 2012

Since the optimized use of sonar systems available for detection is a very practical problem for a given ocean environment, the measure of mission achievability is needed for operating the sonar system efficiently. In this paper, a theory on Measure Of Effectiveness(MOE) for specific mission such as detection is described as the measure of mission achievability, and a recursive Cumulative Detection Probability(CDP) algorithm is found to be most efficient from comparing three CDP algorithms for discrete glimpses search to reduce computation time and memory for complicated scenarios. The three CDPs which are MOE for sonar-maneuver pattern are calculated as time evolves for comparison, based on three different formula depending on the assumptions as follows; dependent or independent glimpses, unimodal or non-unimodal distribution of Probability of Detection(PD) as a function of observation time interval for detection. The proposed CDP algorithm which is made from unimodal formula is verified and applied to OASPP(Optimal Acoustic Search Path Planning) with complicated scenarios.

• Journal of the Korea Institute of Military Science and Technology
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• v.16 no.1
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• pp.5-26
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• 2013

Since the optimized use of sonar systems for target tracking is a practical problem for naval operations, the measure of mission achievability is needed for preparing efficient sonar-maneuver tactic. In order to quantify the mission achievability or Measure Of Effectiveness(MOE) for given sonar-maneuver tactics, we developed and tested a simulation algorithm. The proposed algorithm for tracking is based on Measure Of Performance(MOP) for localization and tracking system of sonar against target. Probability of Detection(PD) using steering beam patterns referenced to the aspect angle of sonar is presented to consider the tracking-performance of sonar. Also, the integrated software package, named as Optimal Acoustic Search Path Planning(OASPP) is used for generating sonar-maneuver patterns and vulnerability analysis for a given scenario. Through simulation of a simple case for which the intuitive solution is known, the proposed algorithm is verified.