Ball Aerospace & Technologies Corp.

Bae Systems Space & Mission Systems Inc.

Cynthia Wallace

Bevan D Staple

Jennifer H Lee

Gordon C Wu

Todd A Pett

Carl S Weimer

Reuben R Rohrschneider

Sara C Tucker

Lyle Ruppert

Zachary Schmidt

Jarett Levi Bartholomew

William D Tandy

Jason Monnin

Samuel Rivera

Joshua D Funderburg

Jason Monin

Corey Allan Hahn

Olaleye A Aina

David W Draper

Mats D Bennett

Intelligent sensor systems and methods are provided. An intelligent sensor system as described herein includes an intelligent sensor array in which at least portions of a neural network are implemented in hardware. More particularly, multiple artificial intelligence pixels, each providing a neural network, can be included in the intelligent sensor system. Each artificial intelligence pixel includes a plurality of sub-pixel elements disposed across a portion of the intelligent sensor array. Each sub-pixel element includes a photodetector and a neuromorphic element. Weighted outputs from the sub-pixel elements within an artificial intelligence pixel are summed and compared to a reference value. Depending on that comparison, a pixel output is or is not provided to a subsequent layer of a larger neural network or to a data consumer.

Artificial intelligence pixel sensor systems and methods

A multiple functional instrument is provided. The instrument includes an optical autocovariance function interferometer that can feature multiple fields of view to detect winds in the atmosphere. The instrument can include an infrared camera to detect atmospheric temperatures and the presence of clouds, and a detector assembly that detects the polarization of light returned to the interferometer. Data collected by the instrument can be provided to a deep and reinforcement learning algorithm for real-time prediction of clear air turbulence and other wind-based aviation safety phenomena. Moreover, predicted and actual conditions can be correlated and used to train a deep learning algorithm to enable more accurate predictions. The instrument can be carried by an aircraft or other platform and operated to detect clear air turbulence or other atmospheric phenomena, and to provide instructions regarding flight parameters including wind-aided navigation in order to minimize the effect of predicted turbulence.

Optical wind lidar-based multifunctional instrument for enhanced measurements and prediction of clear air turbulence and other wind-based aviation related phenomena

Automated methods and systems for tuning parameters of detectors based on metrics are provided. The tuning methods and systems include using machine learning to adjust registers used for setting detector parameters in an automated fashion to achieve optimal performance in a time-efficient manner. The tuning process can include determining available registers provided by the detector and setting values within those registers to a starting value. A binary search in either direction from the starting value is then performed to determine the limits of the parameter values for each register. The register values can then be optimized in view of selected metrics.

Systems and methods of tuning sensor devices

Systems and methods for forming radio frequency beams in communication systems are provided. Signals from one or more devices are received at a base station and are processed using a vector based deep learning (VBDL) model or network. The VBDL model can receive and process vector and/or spatial information related to or part of the received signals. An optimal beamforming vector for a received signal is determined by the VBDL model, without reference to a codebook. The VBDL model can incorporate parameters that are pruned during training to provide efficient operation of the model.

Systems and methods for enhancing communication network performance using vector based deep learning

Microwave radiometers (MRs) and methods for detecting microwave emissions using an electro-optical receiver that incorporates a photonic integrated circuit are provided. The electro-optical receiver includes an electro-optic modulator that modulates received radio frequency signals onto an optical carrier signal supplied by a pump laser. The resulting upconverted signal, containing the full spectrum of the radio frequency signals, is divided into channels by an optical filter. Each of the channels is connected to a corresponding photodetector, which produces an electrical output having an amplitude that is proportional to the amplitude of the received optical signal. The components included in the photonic integrated circuit can be formed on a single substrate. In addition, the optical filter can filter the received full spectrum optical signal into a large number of channels (e.g. greater than 50).

Microwave radiometer systems and methods with electro-optical conversion in photonic integrated circuits

Imaging systems and methods that implement a deep learning network are disclosed. The deep learning network utilizes pose information associated with at least some identified objects. The network is pruned, to reduce the amount of information processed and to optimize runtime processing when the network is deployed. In operation, the network identifies objects, and propagates pose information for at least some of the objects or components of identified objects. The network can be deployed as part of a processing system of an imaging system included as part of a remote platform.

Optimized focal-plane electronics using vector-enhanced deep learning

Methods and systems for remotely detecting gases and emissions of gases are provided. Data is collected from a scene using a sensor system. The data is initially optionally processed as 1D data to remove noise, and is then assigned a confidence value by processing the 1D data using a neural network. The confidence value is related to a likelihood that an emission has been detected at a particular location. The processed 1D data, including the confidence value, is gridded into 2D space. The 2D data is then processed using a neural network to assign a 2D confidence value. The 2D data can be fused with RGB data to produce a map of emission source locations. The data identifying emissions can also be processed using a neural network to determine and output emission rate data.

Method and systems for remote emission detection and rate determination

Phase correction systems and methods capable of operating in a deployed antenna system are provided. The phase correction system includes a signal generator and a signal coupler. The signal coupler injects a signal at an end of a signal line adjacent an antenna element. Changes in an effective length of the signal line can be detected at a controller that monitors characteristics of the injected signal after it has passed through the signal line. The system can adapt to detected changes in the electrical length by controlling an adjustable phase shifter provided in line with the signal line or by applying suitable post-processing.

Growing community of inventors

Louisville, CO, United States of America

Cynthia Wallace