Direct space-to-information converter for efficient interference sensing

This technology is a reconfigurable and scalable architecture for efficient detection of direction-of-arrival of an interference signal.

Unmet Need: Reducing tradeoff in interference sensing due to the Nyquist sampling theorem

Current methods in direction-of-arrival (DOA) sensing rely on conventional delay-and-sum beamformers (CBFs). While CBF is widely used, it has significant drawbacks, namely scan time, resolution and energy consumption due to the Nyquist sampling theorem. Because detection of a signal requires the placement of several spatial antennas, relying on CBF will require many sum angles and intensive calculations. Thus, in a CBF system, sampling time and performance are tradeoffs when detecting the DOA of an interferer.

The Technology: Reconfigurable and scalable direct space-to-information converters for rapid DOA sensing

This technology is a direct space-to-information converter (DSIC) that unifies conventional beamformers (CBFs) with compressed sampling of DOA into a single reconfigurable and scalable receiver-array architecture. This technology reduces the number of scans required and has increased detection efficiencies compared to CBF. DSIC can rapidly find the DOA of a certain number of emitters by converting an incoming wavefront to spatial information. It then generates only a few compressed sensing measurements by forming random projections of the spatial signal consecutively in time. This technology has been shown to consume 16× less energy than a CBF. In addition, DSIC offers a wide-range of reconfigurability and scalability advantages when compared to CBF, especially when the number of interferers is unknown.

Applications:

  • Efficient direction-of-arrival sensing
  • Cellular communication or GPS interference mitigation
  • Vehicular radar systems (LIDAR)
  • Ultrasound imaging
  • Unmanned aerial vehicle detection

Advantages:

  • Reconfigurable and scalable architecture for signal detection and sensing
  • Faster and lower energy interference signal locating
  • Reduced overhead costs in performance and sampling time

Lab Director:

Peter Kinget, Ph.D.

Patent Information:

Patent Issued

Related Publications:

Tech Ventures Reference:

Quick Facts:
Tags
Compressed sensingEnergyLidarMedical ultrasoundModulationNyquist frequencyNyquist–Shannon sampling theoremPseudorandomnessRadarUnmanned aerial vehicleWavefrontWideband
Inventors
John N. WrightMatthew BajorPeter KingetTanbir Haque
Manager
Greg Maskel
Departments
Electrical Engineering
Divisions
Fu Foundation School of Engineering and Applied Science (SEAS)
Reference Number
CU18364
Release Date
2018-05-16