USA As Represented by Secretary of the Navy

Qualcomm Incorporated

Daniel F Garcia

Heidi L Buck

John Stastny

Chang-Ho Lee

Alvin L Quintana

Bryan D Bagnall

Xiaoju Yu

Francesco Carrara

Mark A Kuhlman

John Jong-Hoon Lee

Stephen L Hobbs

Supatta Niramarnkarn

Michael R Hughes

Erin Joslin

Jason Cole

Ashish Alawani

Kinfegebriel Amera Mengistie

Jeongkeun Kim

Keith Pifko

A package that includes a substrate having a first surface; a solder resist layer coupled to the first surface of the substrate; a device located over the solder resist layer such that a portion of the device touches the solder resist layer; and an encapsulation layer located over the solder resist layer such that the encapsulation layer encapsulates the device. The solder resist layer is configured as a seating plane for the device. The device is located over the solder resist layer such that a surface of the device facing the substrate is approximately parallel to the first surface of the substrate. The solder resist layer includes at least one notch. The device is located over the solder resist layer such that at least one corner of the device touches the at least one notch.

Package comprising a solder resist layer configured as a seating plane for a device

A method involves adapting a vessel detection algorithm based upon received synthetic aperture radar (SAR) image data and associated metadata, detecting one or more vessels within an image tile of the SAR image data by iteratively applying the adapted vessel detection algorithm to successive portions of the image tile, discarding a detected vessel if a false alarm is determined, extracting one or more features from the detected vessels that are not discarded, and generating one or more output products based upon the extracted features.

Adaptive automated synthetic aperture radar vessel detection method with false alarm mitigation

Methods for processing overhead imagery of a vessel include the step of determining an initial classification and classification probability based on the vessel length and length-to-width ratio. Next, mutually exclusive deck features can be extracted from the image. For several embodiments, the extracted deck features that can be spherical tanks, hatches and containers that are stored on deck. The initial classification probability is then weighted using the results of the deck feature extraction step to yield a posterior classification probability for the ship image. If the posterior classification probability is above a predetermined value, the image is assigned a posterior classification. If the posterior probability is below the predetermined value, the vessel image is classified as unknown, and the gross tonnage of the vessel is calculated using the length and width of the vessel.

Method for classifying vessels using features extracted from overhead imagery

The present invention relates to an apparatus for locating objects (such as exploded or unexploded ordnance). The embodiments take advantage of spectroscopic features of an object's paint or surface finish to discriminate between the object and the background area. The apparatus utilizes an optical sensor, filters and the application of pixel to pixel ratios to detect the paint on an object from a distance so that objects such as unexploded ordnance may be safely destroyed or neutralized.

Apparatus for detection of objects

An optical system having a pair of ellipsoidal shaped reflective surfaces or mirrors which receive light from an object and provide wide field view imaging for the object. The optical system directs the light onto a flat detector to a record a wide field of view image of the object on the flat detector.

Confocal ellipsoidal mirror system for wide field of view imaging

Growing community of inventors

Inyokern, CA, United States of America

Daniel F Garcia