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Context-Aware Dynamic Asset Allocation for Maritime Interdiction Operations

机译:海上拦截作战的情境感知动态资产分配

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This paper validates two approximate dynamic programming approaches on a maritime interdiction problem involving the allocation of multiple heterogeneous assets over a large area of responsibility to interdict multiple drug smugglers using heterogeneous types of transportation on the sea with varying contraband weights. The asset allocation is based on a probability of activity surface, which represents spatio-temporal target activity obtained by integrating intelligence data on drug smuggler whereabouts/waypoints for contraband transportation, behavior models, and meteorological and oceanographic information. We validate the proposed architectural and algorithmic concepts via several realistic mission scenarios. We conduct sensitivity analyses to quantify the robustness and proactivity of our approach, as well as to measure the value of information used in the allocation process. The contributions of this paper have been transitioned to and are currently being tested by Joint Interagency Task Force-South, an organization tasked with providing the initial line of defense against drug trafficking in the East Pacific and Caribbean Oceans.
机译:本文针对海上拦截问题验证了两种近似的动态规划方法,该方法涉及在一个较大的责任区域内分配多种异构资产,以利用海上运输中各种违禁品权重的异构类型来拦截多种毒品走私者。资产分配基于活动表面概率,它表示时空目标活动,该活动通过整合有关走私者走私毒品的下落/路线的情报数据,行为模型以及气象和海洋学信息而获得。我们通过几个现实的任务场景来验证所提出的体系结构和算法概念。我们进行敏感性分析,以量化我们的方法的鲁棒性和主动性,以及衡量分配过程中使用的信息的价值。本文的贡献已经移交给南方联合机构间工作队,该组织目前正在测试该工作队,该组织的任务是为抵御东太平洋和加勒比海的毒品贩运提供最初的防线。

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