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首页> 外文会议>Conference on Signal and Data Processing of Small Targets 2002, Apr 2-4, 2002, Orlando, USA >Sensor Resource Management for an Airborne Early Warning Radar
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Sensor Resource Management for an Airborne Early Warning Radar

机译：机载预警雷达的传感器资源管理

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This paper addresses scheduling algorithms to determine optimum utilization of an Airborne Early Warning (AEW) radar timeline resource based on radar constraints. The operation of an AEW surveillance radar in dense overland environments along with the presence of low altitude as well as highly maneuvering targets make detection and tracking a very complex one. A mechanically rotating antenna with electronic scanning capability addresses this problem. Not only does it provide maximum gain in the boresight direction of the antenna, but also the flexibility to focus energy and provide higher update rates at given sectors and selected targets. With the advent of electronic scanning, an efficient means of utilizing the radar timeline and waveforms with the available radar resources is required. To do this, a radar resource management concept is required for future AEW electronic scanning surveillance systems. This paper studies the resource management problem for an antenna with electronic scanning capabilities without rotation. The timeline is formulated in terms of radar dwells and revisit time constraints specified for each surveillance sector. A dwell is defined as radar time on target or angular position and revisit time is defined as the time between radar updates of a particular target or angular position. The methodology provides a criterion for determining if a feasible schedule exists that satisfies the dwell and revisit time constraints as well as methods for computing such schedules. The investigation includes the structure of optimal schedules and the complexity of the problem. Several solution techniques have been developed. The first algorithm developed is exact and it is based on dynamic programming. Since the problem is NP-hard, this algorithm is efficient for a small number of sectors. In order to solve medium and large size problems, heuristic approaches have been pursued. The heuristic developed is based on constrained semi-Markov decision processes. First, a relaxed version of the problem utilizing average re-visit time constraints is used rather than solving the problem in a rigorous way. Search methods are then used to find a rigorous solution.
机译：本文提出了基于雷达约束来确定机载预警（AEW）雷达时间轴资源最佳利用的调度算法。 AEW监视雷达在密集的陆地环境中的运行以及低空以及机动性强的目标的存在，使得检测和跟踪非常复杂。具有电子扫描功能的机械旋转天线解决了这个问题。它不仅可以在天线的视轴方向上提供最大增益，而且还可以灵活地集中能量并在给定扇区和选定目标上提供更高的更新率。随着电子扫描的出现，需要一种利用雷达时间线和波形以及可用雷达资源的有效手段。为此，未来的AEW电子扫描监视系统需要雷达资源管理概念。本文研究了具有电子扫描能力且不旋转的天线的资源管理问题。根据雷达停留时间和为每个监视部门指定的重新访问时间限制来制定时间线。停留时间定义为目标或角度位置上的雷达时间，重访时间定义为特定目标或角度位置的雷达更新之间的时间。该方法提供了用于确定是否存在满足暂停和重新访问时间约束的可行时间表的标准，以及用于计算此类时间表的方法。调查包括最佳计划的结构和问题的复杂性。已经开发了几种解决方案技术。开发的第一个算法是精确的，它是基于动态编程的。由于问题是NP难题，因此该算法对少量扇区有效。为了解决中型和大型的问题，已经探索了启发式方法。启发式算法是基于约束的半马尔可夫决策过程而开发的。首先，使用的是利用平均重新访问时间限制的问题的宽松版本，而不是严格地解决问题。然后使用搜索方法找到严格的解决方案。

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