公开(公告)号：US11756287B2

公开(公告)日：2023-09-12

申请号：US17572485

申请日：2022-01-10

Applicant: Raytheon Company

Inventor： Christopher M. Pilcher ,  Christopher Harris ,  John R. Goulding ,  William D. Weaver

IPC: G06V10/40 ,  G06F18/241

CPC classification number: G06F18/241 ,  G06V10/40 ,  G06V2201/07

Abstract: An automatic target recognizer system including: a database that stores target recognition data including multiple reference features associated with each of multiple reference targets; a pre-selector that selects a portion of the target recognition data based on a reference gating feature of the multiple reference features; a preprocessor that processes an image received from an image acquisition system which is associated with an acquired target and determines an acquired gating feature of the acquired target; a feature extractor and processor that discriminates the acquired gating feature with the reference gating feature and, if there is a match, extracts multiple segments of the image and detects the presence, absence, probability or likelihood of one of multiple features of each of the multiple reference targets; a classifier that generates a classification decision report based on a determined classification of the acquired target; and a user interface that displays the classification decision report.

公开(公告)号：US11468332B2

公开(公告)日：2022-10-11

申请号：US15810946

申请日：2017-11-13

Applicant: Raytheon Company

Inventor： John R. Goulding ,  John E. Mixter ,  David R. Mucha ,  Troy A. Gangwer ,  Ryan D. Silva

IPC: G06N3/08 ,  G06N3/04 ,  G06N3/063

Abstract: Processing circuitry for a deep neural network can include input/output ports, and a plurality of neural network layers coupled in order from a first layer to a last layer, each of the plurality of neural network layers including a plurality of weighted computational units having circuitry to interleave forward propagation of computational unit input values from the first layer to the last layer and backward propagation of output error values from the last layer to the first layer.

公开(公告)号：US20190087708A1

公开(公告)日：2019-03-21

申请号：US15711457

申请日：2017-09-21

Applicant: Raytheon Company

Inventor： John R. Goulding ,  John E. Mixter ,  David R. Mucha

IPC: G06N3/04 ,  G06F12/0817

Abstract: A dynamically adaptive neural network processing system includes memory to store instructions representing a neural network in contiguous blocks, hardware acceleration (HA) circuitry to execute the neural network, direct memory access (DMA) circuitry to transfer the instructions from the contiguous blocks of the memory to the HA circuitry, and a central processing unit (CPU) to dynamically modify a linked list representing the neural network during execution of the neural network by the HA circuitry to perform machine learning, and to generate the instructions in the contiguous blocks of the memory based on the linked list.

公开(公告)号：US12130888B2

公开(公告)日：2024-10-29

申请号：US17520000

申请日：2021-11-05

Applicant: Raytheon Company

Inventor： Crystal D. Rhodes ,  John R. Goulding ,  Christopher M. Pilcher ,  Christopher R. Harris

IPC: G06F18/214 ,  G06F18/213 ,  G06F18/24 ,  G06N20/00 ,  G06T7/73 ,  G06V10/40

CPC classification number: G06F18/214 ,  G06F18/213 ,  G06F18/24 ,  G06N20/00 ,  G06T7/73 ,  G06V10/40 ,  G06T2207/20081

Abstract: Devices, systems, and methods for machine learning model generation. A method can include generating image chips of an image. The image chips can each provide a view of a different extent of an object in the image. Based on an object definition that indicates respective features of the object and a location of the respective features along a length of the object, it can be determined whether any of the image chips include any of the respective features. Each image chip of the image chips can be labeled to include an indication of any of the features included in the image chip resulting in labelled image chips. The method can include training an ensemble classifier based on the labelled image chips resulting in a trained ensemble classifier.

公开(公告)号：US11222245B2

公开(公告)日：2022-01-11

申请号：US16887508

申请日：2020-05-29

Applicant: Raytheon Company

Inventor： Christopher M. Pilcher ,  Christopher Harris ,  John R. Goulding ,  William D. Weaver

IPC: G06K9/62 ,  G06K9/46

Abstract: An automatic target recognizer system including: a database that stores target recognition data including multiple reference features associated with each of multiple reference targets; a pre-selector that selects a portion of the target recognition data based on a reference gating feature of the multiple reference features; a preprocessor that processes an image received from an image acquisition system which is associated with an acquired target and determines an acquired gating feature of the acquired target; a feature extractor and processor that discriminates the acquired gating feature with the reference gating feature and, if there is a match, extracts multiple segments of the image and detects the presence, absence, probability or likelihood of one of multiple features of each of the multiple reference targets; a classifier that generates a classification decision report based on a determined classification of the acquired target; and a user interface that displays the classification decision report.

公开(公告)号：US12078718B2

公开(公告)日：2024-09-03

申请号：US17674530

申请日：2022-02-17

Applicant: Raytheon Company

Inventor： Raymond Samaniego ,  John R. Goulding

IPC: G01S13/90

CPC classification number: G01S13/9064 ,  G01S13/9027

Abstract: Devices, systems, and methods for removing non-linearities in an inverse synthetic aperture radar (ISAR) image are provided. A method includes estimating pitch and roll about range and doppler axes of a time series of ISAR images including the ISAR image, interpolating ISAR image data based on the estimated pitch and roll resulting in interpolated ISAR image data, and resampling based on the interpolated ISAR image data and the time series of TSAR images resulting in an enhanced image.

公开(公告)号：US20210374485A1

公开(公告)日：2021-12-02

申请号：US16887508

申请日：2020-05-29

Applicant: Raytheon Company

Inventor： Christopher M. Pilcher ,  Christopher Harris ,  John R. Goulding ,  William D. Weaver

IPC: G06K9/62 ,  G06K9/46

Abstract: An automatic target recognizer system including: a database that stores target recognition data including multiple reference features associated with each of multiple reference targets; a pre-selector that selects a portion of the target recognition data based on a reference gating feature of the multiple reference features; a preprocessor that processes an image received from an image acquisition system which is associated with an acquired target and determines an acquired gating feature of the acquired target; a feature extractor and processor that discriminates the acquired gating feature with the reference gating feature and, if there is a match, extracts multiple segments of the image and detects the presence, absence, probability or likelihood of one of multiple features of each of the multiple reference targets; a classifier that generates a classification decision report based on a determined classification of the acquired target; and a user interface that displays the classification decision report.

公开(公告)号：US20230419640A1

公开(公告)日：2023-12-28

申请号：US17827096

申请日：2022-05-27

Applicant: Raytheon Company

Inventor： Suhail Shabbir Saquib ,  Christopher M. Pilcher ,  John R. Goulding

IPC: G06V10/764 ,  G06V20/17 ,  G06V10/22

CPC classification number: G06V10/764 ,  G06V20/17 ,  G06V10/235

Abstract: Devices, systems, and methods for machine learning (ML) automatic target recognition (ATR) decision explanation are provided. A method can include receiving an object specification matrix from an object model database that indicates, for each of a plurality of physical portions of an object, whether each of a plurality of features are present or absent in a physical portion of the physical portions of the object and a proportional physical displacement between the features in the object, receiving feature data indicating for an image of a portion of the object, a likelihood whether each of features are present in the image, determining based on the object specification matrix and the feature data, a probability and corresponding uncertainty that the image corresponds to the object, and providing the probability and corresponding uncertainty of the object to help classify the object.

公开(公告)号：US20190147342A1

公开(公告)日：2019-05-16

申请号：US15810946

申请日：2017-11-13

Applicant: Raytheon Company

Inventor： John R. Goulding ,  John E. Mixter ,  David R. Mucha ,  Troy A. Gangwer ,  Ryan D. Silva

IPC: G06N3/08 ,  G06N3/04 ,  G06N3/063

Abstract: Processing circuitry for a deep neural network can include input/output ports, and a plurality of neural network layers coupled in order from a first layer to a last layer, each of the plurality of neural network layers including a plurality of weighted computational units having circuitry to interleave forward propagation of computational unit input values from the first layer to the last layer and backward propagation of output error values from the last layer to the first layer.

公开(公告)号：US20230258796A1

公开(公告)日：2023-08-17

申请号：US17674530

申请日：2022-02-17

Applicant: Raytheon Company

Inventor： Raymond Samaniego ,  John R. Goulding

IPC: G01S13/90

CPC classification number: G01S13/9064 ,  G01S13/9027

Abstract: Devices, systems, and methods for removing non-linearities in an inverse synthetic aperture radar (ISAR) image are provided. A method includes estimating pitch and roll about range and doppler axes of a time series of ISAR images including the ISAR image, interpolating ISAR image data based on the estimated pitch and roll resulting in interpolated ISAR image data, and resampling based on the interpolated ISAR image data and the time series of TSAR images resulting in an enhanced image.