Solutions
Orientation Tracking
Inertial Tracking System that produces stable Augmented Reality (AR) imagery and accurate heading in the presence of difficult magnetic disturbances.
Features:
- Accuracy to within 0.4 degree (standard deviation)
- Standard C based implementation portable to various processors
- Calibration routines and simulator available
- Tunable parameters for adapting to new products and conditions
- Customizable architecture allows additional sensors
Spectrum Sensing
SPT's Spectrum Sensing technology takes a wideband RF collection, produces time/frequency bounding boxes and performs characterization of each detected signal.
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Features:
- Detection of LPI/LPD Signals
- Detection of low SNR Signals
- Adaptable for different data collectors
- Multiantenna/spatial add-ons available
- Adaptable for different processing architectures
- Low processing resources required (100 MHz continuous monitoring on CPUs)
AI Restoration for Impaired Signal Extraction (ARISE)
RF Front-ends suffer significant distortion when the signals are more powerful than expected, resulting in distorted digital signals. ARISE restores the signals and allows downstream processing to work correctly.
Features:
- Effectively increases the dynamic ranges of receivers
- Reconstructs signals operating up to 40 dB past the RF Front-End linear region
- Implemented for either General Purpose Processors or Graphic Processing Units
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Applications:
- Radar Warning Receivers, Low C-SWAP RF, Wideband Sensing, Bi-Static Radar
Anomaly Detection and Characterization
RF spectrum is so dense with rapidly changing signals that no human can view the spectrogram and accurately find new signals. SPT’s automatic signal detection and characterization reduces detection information to enable users to isolate new or anomalous signals.
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Features:
- Detects everything in the RF spectrum from DC to 6 Ghz
- Surprisal metric pulls out signals different from the background training captures
- User in the loop interface allows clicking on a signal for further analysis, such as cyclostationary processing, to create better future detectors
