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Calibrated and geocoded clutter from an airborne multispectral scanner

机译:来自空中多光谱扫描仪的校准和地理统一杂乱

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Robustness of automatic target recognition (ATR) to varying observation conditions and countermeasures is substantially increased by use of multispectral sensors. Assessment of such ATR systems is performed by captive flight tests and simulations (HWIL or complete modeling). Although the clutter components of a scene can be generated with specified statistics, clutter maps directly obtained from measurement are required for validation of a simulation. In addition, urban scenes have non-stationary characteristics and are difficult to simulate. The present paper describes a scanner, data acquisition and processing system used for the generation of realistic clutter maps incorporating infrared, passive and active millimeter wave channels. The sensors are mounted on a helicopter with coincident line-of-sight, enabling us to measure consistent clutter signatures under varying observation conditions. Position and attitude data from GPS and an inertial measurement unit, respectively, are used to geometrically correct the raw scanner data. After sensor calibration the original voltage signals are converted to physical units, i.e. temperatures and reflectivities, describing the clutter independently of the scanning sensor, thus allowing us the use of the clutter maps in tests of a priori unknown multispectral sensors. The data correction procedures are described and results are presented.
机译:通过使用多光谱传感器,自动目标识别(ATR)的自动目标识别(ATR)的鲁棒性显着增加。对此类ATR系统的评估是由俘弧飞行测试和模拟(HWIL或完全建模)执行的。尽管场景的杂波组分可以用指定的统计生成,但是需要从测量中直接获得的杂乱映射来验证模拟。此外,城市场景具有非静止特性,难以模拟。本文介绍了一种用于生成结合红外线,被动和活动毫米波通道的现实杂波贴图的扫描仪,数据采集和处理系统。传感器安装在一架直升机上,其具有一致的视线,使我们能够在不同观察条件下测量一致的杂波签名。来自GPS和惯性测量单元的位置和姿态数据分别用于几何校正原始扫描仪数据。传感器校准后的原来的电压信号被转换为物理单元,即温度和反射率,独立地扫描传感器的描述杂波,从而使我们在先验未知多光谱传感器的测试使用杂波地图。描述了数据校正过程并呈现结果。

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