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Assessing resource requirements for maritime domain awareness and protection (security)

机译:评估海域意识和保护(安全)的资源需求

摘要

A maritime domain or region contains a number w of nonhostile W (White) vessels of interest. Hostile R (Red) vessels enter the domain. The Rs are traveling through the domain toward targets. Overhead, friendly (Blue) sensors (S) patrol the domain and classify (perhaps incorrectly) detected vessels of interest as R or W. The misclassification of a W as an R is a false positive. An overhead sensor follows (or tracks) any vessel it classifies as R until it is relieved by another platform, perhaps a destroyer pair (DD). The overhead sensor is here assumed unable to detect and classify additional vessels while it is following a suspicious vessel; this may well be a somewhat pessimistic assumption, very possibly richer possibilities based on additional assets (such as unmanned aerial vehicles (UAVs)) are available, but loss of track may occur as well as misclassification. Deterministic and stochastic models are formulated and studied to evaluate the probability that Rs are successfully neutralized before reaching their destination. The model results quantify the effect of the resources and time needed to prosecute misclassified Ws (false positives) on the probability of successfully neutralizing R. The results indicate that the probability of neutralizing an R vessel is very sensitive to the false positive rate. Technologies, processes, and procedures that can decrease the false positive rate will increase the effectiveness of the Maritime Intercept Operation (MIO).-- p. iii.
机译:海域或区域包含许多w所关注的非敌对W(白色)船只。敌对的R(红色)船只进入域。 Rs通过域朝目标行进。高架,友好的(蓝色)传感器(S)在域中巡逻,并将检测到的感兴趣的血管分类(可能错误地分类为R或W)。将W错误分类为R是误报。高架传感器跟踪(或跟踪)其归类为R的任何船只,直到被另一个平台(可能是驱逐舰对(DD))释放。在这里,假定高架传感器在跟随可疑船只时无法检测和分类其他船只;这可能是一个有点悲观的假设,基于其他资产(例如无人飞行器(UAV))的可能性可能会非常丰富,但可能会发生航迹丢失和分类错误的情况。建立并研究确定性和随机模型,以评估Rs在到达目的地之前成功中和的可能性。模型结果量化了起诉错误分类的Ws(假阳性)所需的资源和时间对成功中和R的概率的影响。结果表明,中和R容器的概率对假阳性率非常敏感。可以降低误报率的技术,过程和程序将提高海上拦截行动(MIO)的有效性。 iii。

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