公开(公告)号：US09279724B2

公开(公告)日：2016-03-08

申请号：US14312740

申请日：2014-06-24

Applicant: RAYTHEON COMPANY

Inventor： Ian S. Robinson ,  John D. Bloomer ,  Bradley Flanders

IPC: G01J3/45 ,  G01J3/453 ,  G01J3/02 ,  G01J3/06

CPC classification number: G01J3/4535 ,  G01J3/0202 ,  G01J3/06 ,  G01J3/45 ,  G01J2003/4538

Abstract: Interferometric transform spectrometer (ITS) systems and methods of operation thereof. In one example, an ITS system includes a Michelson interferometer that introduces a varying optical path length difference (OPD) between its two arms so as to produce an interferogram, a detector that receives and samples the interferogram, and a scan controller coupled to the detector and to Michelson interferometer. The scan controller controls the Michelson interferometer to vary the OPD in discrete steps such that the detector provides M samples of the interferogram for each of two scan segments. In the first scan segment, the M samples have a uniform or non-uniform sample spacing and the OPD has a first maximum value. In the second scan segment, the M samples have an incrementally increasing sample spacing and the OPD has a second maximum value that is at least twice the first maximum value.

Abstract translation: 干涉测量变换光谱仪（ITS）系统及其操作方法。 在一个示例中，ITS系统包括迈克尔逊干涉仪，其在其两个臂之间引入变化的光程长度差（OPD），以产生干涉图，接收和采样干涉图的检测器，以及耦合到检测器的扫描控制器 和迈克尔逊干涉仪。 扫描控制器控制迈克尔逊干涉仪以离散步骤改变OPD，使得检测器为两个扫描段中的每一个提供干涉图的M个采样。 在第一扫描段中，M个样本具有均匀或不均匀的采样间隔，并且OPD具有第一最大值。 在第二扫描段中，M个采样具有逐渐增加的采样间隔，并且OPD具有至少为第一最大值的两倍的第二最大值。

公开(公告)号：US09213913B1

公开(公告)日：2015-12-15

申请号：US14561873

申请日：2014-12-05

Applicant: Raytheon Company

Inventor： Ian S. Robinson ,  Bradley Flanders ,  Anthony Sommese

IPC: G06K9/00 ,  G06K9/46 ,  G06K7/14 ,  G06K9/40 ,  G06T5/20 ,  G06K9/62 ,  G06F17/16

CPC classification number: G06K9/46 ,  G06F17/16 ,  G06K7/146 ,  G06K9/00557 ,  G06K9/0063 ,  G06K9/40 ,  G06K9/4609 ,  G06K9/6232 ,  G06K2009/00644 ,  G06K2009/4657 ,  G06T5/20 ,  G06T2207/10028

Abstract: A rapid target detection approach with corresponding method and system to detect targets in scene pixels, efficiently, is presented. The approach includes tailoring an approximation of a target score for each scene pixel, individually, based on an “intermediate target score.” The intermediate target score includes a portion of the terms used to compute the target score. The portion is selected by computing a signal-to-clutter ratio (SCR) for a spectral reference associated with a target and ranking the terms by their contribution to the SCR. Scene pixels with low intermediate target scores are removed from further processing. The remaining scene pixels are further processed, including computing target scores to detect targets in these scene pixel. Advantageously, examples of the approach process a few terms of all scene pixels, eliminate most scene pixels, and calculate more terms on high target scoring scene pixels as needed.

Abstract translation: 提出了一种快速目标检测方法，具有相应的方法和系统，有效地检测场景像素中的目标。 该方法包括基于“中间目标得分”单独地定制每个场景像素的目标分数的近似值。中间目标分数包括用于计算目标分数的术语的一部分。 通过计算与目标相关联的频谱参考的信号与杂波比（SCR）来选择该部分，并通过它们对SCR的贡献来对这些项进行排序。 具有低中等目标分数的场景像素从进一步处理中移除。 剩余的场景像素被进一步处理，包括计算目标分数以检测这些场景像素中的目标。 有利地，所述方法的示例处理所有场景像素的几个术语，消除大多数场景像素，并且根据需要在高目标评分场景像素上计算更多项。

公开(公告)号：US09147126B2

公开(公告)日：2015-09-29

申请号：US13957415

申请日：2013-08-01

Applicant: RAYTHEON COMPANY

Inventor： Ian S. Robinson ,  Bradley Flanders ,  Anthony Sommese

IPC: G06K9/62 ,  G06K9/00

CPC classification number: G06K9/6202 ,  G06K9/0063 ,  G06K2009/00644

Abstract: Provided are examples of a detecting engine for identifying detections in compressed scene pixels. For a given compressed scene pixel having a set of M basis vector coefficients, set of N basis vectors, and code linking the M basis vector coefficients to the N basis vectors, the detecting engine reduces a spectral reference (S) to an N-dimensional spectral reference (SN) based on the set of N basis vectors. The detecting engine computes an N-dimensional spectral reference detection filter (SN*) from SN and the inverse of an N-dimensional scene covariance (CN). The detecting engine forms an M-dimensional spectral reference detection filter (SM*) from SN* based on the compression code and computes a detection filter score based on SM*. The detecting engine compares the score to a threshold and determines, based on the comparison, whether the material of interest is present in the given compressed scene pixel and is a detection.

Abstract translation: 提供了用于识别压缩场景像素中的检测的检测引擎的示例。 对于具有M个基矢量系数集合，N个基矢量的集合以及将M个基矢量系数链接到N个基矢量的代码的给定压缩场景像素，检测引擎将频谱参考（S）减小到N维 基于N个基矢量的集合的频谱参考（SN）。 检测引擎计算SN的N维频谱参考检测滤波器（SN *）和N维场景协方差（CN）的倒数。 检测引擎基于压缩码从SN *形成M维频谱参考检测滤波器（SM *），并根据SM *计算检测滤波器分数。 检测引擎将得分与阈值进行比较，并且基于比较确定感兴趣的材料是否存在于给定的压缩场景像素中并且是检测。