Airborne sensor platforms are becoming increasingly significant for both civilian and military operations; yet, at present, their sensors are typically idle for much of their flight time, e.g., while the sensor-equipped platform is in transit to and from the locations of sensing tasks. The sensing needs of many other potential information consumers might thus be served by sharing such sensors, thereby allowing other information consumers to opportunistically task them during their otherwise unscheduled time, as well as enabling other improvements, such as decreasing the number of platforms needed to achieve a goal and increasing the resilience of sensor tasks through duplication. We have implemented a prototype system realizing these goals in Mission-Driven Tasking of Information Producers (MTIP), which leverages an agent-based representation of tasks and sensors to enable fast, effective, and adaptive opportunistic sharing of airborne sensors. Using a simulated large-scale disaster-response scenario populated with publicly available Geographic Information System (GIS) datasets, we demonstrate that correlations in task location are likely to lead to a high degree of potential for sensor-sharing. We then validate that our implementation of MTIP can successfully carry out such sharing, showing that it increases the number of sensor tasks served, reduces the number of platforms required to serve a given set of sensor tasks, and adapts well to radical changes in flight path.

中文翻译：

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自适应机会型机载传感器共享

机载传感器平台对于民用和军事行动都变得越来越重要；然而，目前，他们的传感器通常在大部分飞行时间内处于空闲状态，例如，当配备传感器的平台往返于传感任务的位置时。因此，可以通过共享此类传感器来满足许多其他潜在信息消费者的传感需求，从而允许其他信息消费者在他们原本计划外的时间内有机会地对他们进行任务，并实现其他改进，例如减少实现所需的平台数量目标并通过重复增加传感器任务的弹性。我们已经实现了一个原型系统，在信息生产者的任务驱动任务（MTIP）中实现了这些目标，它利用基于代理的任务和传感器表示来实现机载传感器的快速、有效和自适应机会共享。使用由公开可用的地理信息系统 (GIS) 数据集填充的模拟大规模灾难响应场景，我们证明任务位置的相关性可能会导致传感器共享的高度潜力。然后，我们验证了我们的 MTIP 实现可以成功地进行这种共享，表明它增加了服务的传感器任务的数量，减少了服务给定传感器任务集所需的平台数量，并很好地适应了飞行路径的根本变化. 使用由公开可用的地理信息系统 (GIS) 数据集填充的模拟大规模灾难响应场景，我们证明任务位置的相关性可能会导致传感器共享的高度潜力。然后，我们验证了我们的 MTIP 实现可以成功地进行这种共享，表明它增加了服务的传感器任务的数量，减少了服务给定传感器任务集所需的平台数量，并很好地适应了飞行路径的根本变化. 使用由公开可用的地理信息系统 (GIS) 数据集填充的模拟大规模灾难响应场景，我们证明任务位置的相关性可能会导致传感器共享的高度潜力。然后，我们验证了我们的 MTIP 实现可以成功地进行这种共享，表明它增加了服务的传感器任务的数量，减少了服务给定传感器任务集所需的平台数量，并很好地适应了飞行路径的根本变化.