KEYWORDS: Infrared signatures, Data modeling, Sensors, Infrared radiation, Data archive systems, Thermography, Infrared imaging, Data storage, Data conversion, Cameras
Aircraft self-protection against heat seeking missile threats is an extremely important topic worldwide, recently even more so with the instability in the Middle East region due to, for example, the large number of man-portable air defense systems (MANPADS) that were stolen from army arsenals. A fundamental step in successfully achieving self-protection is the ability to capture and identify aircraft infrared signatures. This work discusses some of our efforts and results in creating an asset database for infrared signatures. The database was designed in a way that will feed an image processing engine to allow for automated feature and signature extraction. A common failing in the handling of target signature raw data is the fact that raw data files can become unreadable because of changes in technology, software applications or weak media archiving technology (e.g. corrupt DVD media). A second shortcoming is often the fact that large volumes of raw or processed data are stored in an unstructured manner, resulting in poor recall later. A third requirement is the portability of data between various processing software packages, legacy, current and future. This paper demonstrates how the challenge of future-proofing measured data is met with reference to the archiving and analysis of data from a recent measurement campaign. Recommendations for future work are given, based on the experience gained.
Saudi Arabia has borders covering over 4,300 km that are shared with seven countries. Such large borders pose many challenges for security and patrol. Thermal imagers are considered the most reliable means of threat detection, however, they are quite costly, which can prevent using them over large areas. This work discusses a multi-sensor acoustic and optical implementation for threat detection as an effort to reduce system cost. The acoustic sensor provides position and direction recognition by using a four microphone setup. The data analysis of field tests will be discussed in this work.
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