A sub-space projection algorithm (SSP) for the suppression of clutter noise created by sensor platform jitter and drift has been evaluated in nine different infrared bands between 2 and 5 /spl mu/m. Earth background scenes were simulated using the Strategic Scene Generation Model (SSGM) and clutter noise generated at three different jitter levels up to 1 pixel in length. The effectiveness of the SSP method in removing the background noise under these conditions was evaluated by first superimposing a target signal and then extracting it before and after noise suppression. Algorithm performance ratings are based both on noise statistics and target signal loss criteria. The algorithm is found to provide factors of 2 to 10 improvement in signal to noise under stressing conditions thus offering an alternative software solution to one particular class of sensor stabilization problems.
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机译：在2个和5个/ spl mu / m之间的9个不同的红外波段中，已经评估了一种用于抑制由传感器平台的抖动和漂移产生的杂波噪声的子空间投影算法（SSP）。使用战略场景生成模型（SSGM）对地球背景场景进行了模拟，并以三种不同的抖动级别（最长1个像素）生成了杂波噪声。通过首先叠加目标信号，然后在抑制噪声之前和之后提取目标信号，来评估SSP方法在这些条件下消除背景噪声的有效性。算法性能等级基于噪声统计数据和目标信号损耗标准。发现该算法可在压力条件下将信噪比提高2到10倍，从而为一类特定的传感器稳定性问题提供了替代软件解决方案。
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