ARTIFICIAL INTELLIGENCE RADIO CLASSIFIER AND IDENTIFIER

    公开(公告)号:US20220217619A1

    公开(公告)日:2022-07-07

    申请号:US17142800

    申请日:2021-01-06

    Abstract: A system whereby individual RF emitter devices are distinguished in real-world environments through deep-learning comprising an RF receiver for receiving RF signals from a plurality of individual devices; a preprocessor configured to produce complex-valued In-phase (I) and Quadrature (Q) IQ signal sample representations; a two-stage Augmented Dilated Causal Convolution (ADCC) network comprising a stack of dilated causal convolution layers and traditional convolutional layers configured to process I and Q components of the complex IQ samples; transfer learning comprising a classifier and a cluster embedding dense layer; unsupervised clustering whereby the RF signals are grouped according to a device that transmitted the RF signal; and an output identifying the individual RF emitter device whereby the individual RF emitter device is distinguished in the real-world environment.

    UTILIZING MULTIPATH TO DETERMINE DOWN AND REDUCE DISPERSION IN PROJECTILES

    公开(公告)号:US20220179034A1

    公开(公告)日:2022-06-09

    申请号:US17112118

    申请日:2020-12-04

    Abstract: A method for launching a round from an airborne platform, receiving a plurality of RF signals at the round, determining an amount of time between a first and second received RF signal, where the second signal is a multi-path signal and the first signal is a direct path signal. An altitude of the round is determined based on the delay between the first and second received signal and aligning the round's flight path with an initial velocity vector of the aircraft platform to reduce dispersion. The round can include a plurality of sensors for detecting the RF signals. The second received RF signal may be a multi-path signal having been reflected off of the earth's surface or another object on the earth's surface. The altitude of the round can be determined using the known altitude of the airborne platform, the delay of time between the first and second received signals, and the speed of light.

    NARROW BAND ANTENNA HARMONICS FOR GUIDANCE IN MULTIPLE FREQUENCY BANDS

    公开(公告)号:US20220178659A1

    公开(公告)日:2022-06-09

    申请号:US17112012

    申请日:2020-12-04

    Abstract: A narrow band antenna is configured to guide a munition toward a target location during a flight of the munition from a launch location toward the target location. The antenna has a first mode of operation operable during a first portion of the flight at a first bandwidth, and a second mode of operation operable during a second portion of the flight at a second bandwidth, the second bandwidth being a harmonic of the first bandwidth, and may be a third harmonic of the first bandwidth. The method includes transmitting a target location information to the munition in the first bandwidth during the first portion of the flight and then transmitting the target location information to the munition in the second bandwidth during the second portion of the flight. The first band may be X-band and the second band may be Ka-band.

    ULTRA-SHORT PULSE MID AND LONG WAVE INFRARED LASER

    公开(公告)号:US20220173568A1

    公开(公告)日:2022-06-02

    申请号:US17109582

    申请日:2020-12-02

    Abstract: The system and method of using an ultra-short pulse mid and long wave infrared laser. The system is seeded with a 2 μm laser source having a pulse duration in the femtosecond range. The beam is stretched, to increase the pulse duration, and the beam is amplified, to increase an energy level of the laser beam. Both mid wave IR and long wave IR seed beams are first generated, and then amplified via one or more optical parametric chirped-pulse amplification stages. A compressor may be used to compress one or more of the output beams to achieve high peak power and controllable pulse duration in the output beams. The output beams may then be used to create atmospheric or material effects at km range.

    REALTIME ELECTRONIC COUNTERMEASURE ASSESSMENT

    公开(公告)号:US20220163628A1

    公开(公告)日:2022-05-26

    申请号:US16953579

    申请日:2020-11-20

    Abstract: A method of assessing the effectiveness of an electronic countermeasure (ECM) applied against an unknown, ambiguous, or unresponsive radar threat includes monitoring changes in a radar-associated factor while applying the ECM and determining if the ECM is disrupting the hostile radar. The radar-associated factor can be a weapon that is controlled by the radar threat, and assessing the ECM can include determining whether the weapon is misdirected due to applying the ECM. Or the radar-associated factor can be a feature of an RF waveform emitted by the radar threat, and assessing the ECM can include determining if the feature is changed due to applying the ECM. Continuous changes in the feature can indicate unsuccessful attempts to mitigate the ECM. Return of the feature to a pre-threat state can indicate disruption of the radar. The ECM can be selected from a library of countermeasures pre-verified as effective against known threats.

    REALTIME ELECTRONIC COUNTERMEASURE OPTIMIZATION

    公开(公告)号:US20220163627A1

    公开(公告)日:2022-05-26

    申请号:US16953568

    申请日:2020-11-20

    Abstract: A method of selecting and optimizing a countermeasure for application against a novel, ambiguous, or unresponsive radar threat includes selecting a candidate countermeasure and an initial parameter set and varying at least one of the parameters while the effectiveness of the candidate countermeasure against the radar threat is assessed, for example by a human observer. Embodiments include repeating the process with additional candidate countermeasures. For an unresponsive radar threat, a previously effective countermeasure can be selected as the candidate countermeasure. For an ambiguous radar threat, at least one countermeasure previously verified as effective against a partially matching known threat can be selected as the candidate countermeasure. Correlated parameters can be simultaneously varied. An optimization surface and trajectory formed by a plurality of correlated parameters can be identified by machine intelligence, used to guide the parameter variations, and/or stored for use against the same or similar threats in the future.

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