Abstract: Star tracker systems and methods are provided. The star tracker incorporates deep learning processes in combination with relatively low cost hardware components to provide moderate (e.g. ˜1 arc second attitude uncertainty) accuracy. The neural network implementing the deep learning processes can include a Hinton's capsule network or a coordinate convolution layer to maintain spatial relationships between features in images encompassing a plurality of features. The hardware components can be configured to collect a blurred or defocused image in which point sources of light appear as blurs, and in which the blurs create points of intersection. Alternatively or in addition, a blurred or defocused image can be created using processes implemented as part of application programming. The processing of collected images by a neural network to provide an attitude determination can include analyzing a plurality of blurs and blur intersections across an entire frame of image data.

Abstract: An antenna system with integrated electromagnetic interference (EMI) shielded heat sink is disclosed. The system includes an antenna circuit board with a plurality of antenna or radiating elements formed on a common plane comprising a first surface. Circuit elements are placed on a second surface of the antenna circuit board. In addition, the second surface of the antenna circuits board is connected to a pocketed EMI shielding cover with individual shield pockets serving as an EMI shield and a heat sink containing a cooling fluid. At least some adjacent pockets can be in fluid communication with one another.

Abstract: 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.

Abstract: Heat transfer systems and methods are provided. The heat transfer system includes an evaporator section integrated with or thermally joined to a heat dissipating system. The evaporator section is connected to a condenser section by a conduit. Together, portions of the evaporator section, the condenser section, and the conduit form a closed volume containing a heat transfer fluid. A superhydrophobic surface is present on at least a portion of the condenser section forming a part of the closed volume. The superhydrophobic surface can include a plurality of carbon nanotubes. The carbon nanotubes can be provided as a forest of carbon nanotubes extending from a rough surface.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: Free-space communication systems and methods are provided. The systems include a transmitter that combines multiple sets of radio-frequency-modulated optical carrier frequencies for transmission across free space using multiple transmission apertures. Different sets of signals are filtered to form single sideband signals. The different sets of single sideband signals are then combined to form dense wavelength division multiplexed signals. In addition, combined sets of signals of different polarizations can be combined. A receiver can include a single receive aperture.

Abstract: A calibration system for sensors is provided. The calibration system includes an array of blackbody elements. Each blackbody element includes a high emissivity surface. The high emissivity surface can be formed using carbon nanotubes. In addition, each blackbody element includes a heating element and a temperature sensor. The heating element is operated to bring the blackbody element to a set point temperature, as determined by the temperature sensor. As an example, the calibration system can be used in connection with sensors sensitive to infrared wavelengths that is carried by a satellite or other platform.

Abstract: Free-space communication systems and methods are provided. The systems include a transmitter that combines multiple sets of radio-frequency-modulated optical carrier frequencies for transmission across free space using multiple transmission apertures. Different sets of signals are filtered to form single sideband signals. The different sets of single sideband signals are then combined to form dense wavelength division multiplexed signals. In addition, combined sets of signals of different polarizations can be combined. A receiver can include a single receive aperture.

Abstract: A microelectromechanical (MEM) capacitance pressure sensor integrated with electronic circuitry on a common substrate and a method for forming such a device are disclosed. The MEM capacitance pressure sensor includes a capacitance pressure sensor formed at least partially in a cavity etched below the surface of a silicon substrate and adjacent circuitry (CMOS, BiCMOS, or bipolar circuitry) formed on the substrate. By forming the capacitance pressure sensor in the cavity, the substrate can be planarized (e.g. by chemical-mechanical polishing) so that a standard set of integrated circuit processing steps can be used to form the electronic circuitry (e.g. using an aluminum or aluminum-alloy interconnect metallization).