Artificial intelligence implementation for multi-domain sensor suite optimization

被引:1
|
作者
Arnous, Ferris, I [1 ]
Narayanan, Ram M. [2 ]
Li, Bing C. [3 ]
机构
[1] Penn State Univ, Dept Engn Sci & Mech, University Pk, PA 16802 USA
[2] Penn State Univ, Dept Elect Engn, University Pk, PA 16802 USA
[3] Lockheed Martin Corp, Owego, NY 13827 USA
来源
RADAR SENSOR TECHNOLOGY XXIV | 2020年 / 11408卷
关键词
multi-domain sensor fusion; machine learning; radar signal processing; sensor selection; artificial intelligence; MANAGEMENT;
D O I
10.1117/12.2567139
中图分类号
TP7 [遥感技术];
学科分类号
081102 ; 0816 ; 081602 ; 083002 ; 1404 ;
摘要
In the era of big data, it appears imperative that future battle management systems be able to identify, decipher, and prioritize actionable information. This calls for fusing information and synchronizing operations across multiple domains and multiple sensor modalities. Fusing data from a diverse range of sensors across multiple domains is critical for improved situational awareness to enhance warfighters' effectiveness. The basis for analyzing multiple field radar system data in real time remains a challenging yet promising threshold for military operational intelligence. Multiple domain sensor systems used to gather field intelligence requires gathering different types of information processing at required speeds that fall short of human reaction time and cognition. To press the advancement of field intelligence, the analysis, fusion and optimization of multi-domain systems, sensor data analysis is explored using probabilistic machine learning and supplemented heuristic signal processing to provide a basis for multi-system data integration, analysis and sensor suite selection.
引用
收藏
页数:10
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