基于神经网络的攻击后损伤评估系统

P. Wang, L. Menegozzi
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引用次数: 1

摘要

自动损伤评估(ADA)的关键要素将包括用于调查和测量攻击后损伤的地面传感器、连接传感器的通信网络、生存恢复中心(SRC)、用于快速响应的跑道维修小组(或机器人),以及用于执行“搜索和优化”过程的先进信号处理器,以实现“最佳”空军基地恢复计划。为了满足美国空军ADA的要求,ITT航空电子公司已经提出开发一种混合信号处理器。该系统将由算法处理器和神经网络组成。为了提高数据分析的性能,关键的数据分析功能由神经网络实现。由于分布式处理能力的固有特性,神经网络不仅提供了数据分析所需的高吞吐量,而且还实现了容错和优雅退化,这对快速跑道修复计划至关重要
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A neural network based postattack damage assessment system
Key elements of an automated damage assessment (ADA) will include ground-based sensors to survey and measure postattack damages, communication networks to link sensors, a survival recovery center (SRC), a runway repair team (or robots) for rapid response, and advanced signal processors to perform the 'search and optimization' processes for the 'best' airbase recovery plan. To meet the USAF ADA requirements, ITT Avionics has proposed the development of a hybrid signal processor. The system will consist of algorithmic processors and neural networks. To improve DA performance, key DA functions are implemented by neural networks. Due to the intrinsic nature of distributed processing power, the neural network not only provides the high throughput required for DA but it also achieves fault tolerance and graceful degradation, which are extremely important for the Rapid Runway Repair program.<>
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