Sparse Source Separation Algorithms for Spectrum Sharing, Maritime Sensors, and Micro-Doppler Feature Extraction

#radar #communications #shared #spectrum
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This talk examines new sparsity-based filtering and extraction algorithms for spectrum sharing, maritime radar sensing, and bird micro-Doppler identification.  We propose large-scale non-differentiable convex under-determined objective functions with sparse priors, and propose efficient iterative fast-transform and matrix-free solutions to extract multiple signals that overlap in time and frequency.  The proposed algorithms are applied to three different applications where signals overlap in time and frequency, and the number of sources is greater than the number of received signals: 1) Radar-to-Radar and Radar-to-Communications spectrum sharing where both signals are decoded despite overlap in time and frequency,  2) Maritime detection and imaging of endo-clutter maritime targets where the signal return of the target and the clutter overlap in both Doppler frequency and time,  3) Radar bird detection and discrimination, which has many civilian and non-civilian applications such as collision avoidance, false alarm reduction for detection radars, stealthy target detection, classification of military unmanned aerial vehicles (UAVs) and civilian drones, and conservation ecology.


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  • Newark, New Jersey
  • United States 07103
  • Building: ECE Building
  • Room Number: ECE CR202
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  • Co-sponsored by North Jersey Section, MTT
  • Starts 07 November 2019 01:00 AM UTC
  • Ends 05 December 2019 01:00 PM UTC
  • No Admission Charge

  Speakers

Masoud Farshchain, Phd Masoud Farshchain, Phd of APS

Biography:

Masoud Farshchian obtained his Bachelor of Science in Electrical Engineering and minor in mathematics from Rutgers University in the year 2000.  From 2000 to 2001, he worked as a systems engineer in Motorola Corporation.  In 2001, he entered graduate school in Rensselaer Polytechnic Institute and obtained a masters in Electrical Engineering in 2003, a masters in applied mathematics in 2005 and his Ph.D. in Electrical Engineering in 2007.  He has a combined 15 years of experience in radar and wireless communications including 5 years in the Radar division of the Naval Research Laboratory, and 2 years in the John Hopkins Applied Physics Laboratory.  His general interest is in the field of signal processing and machine learning with recent specific focus on sensor-to-sensor and sensor-to-communications spectrum sharing.  He has also been active in research and development of maritime detection radar, inverse synthetic aperture radar, sea and bird clutter modeling, image compression, processing and transmission, and wireless communications performance modeling.  Since early 2018, he is with BAE Systems Inc. in Totowa, New Jersey.

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Agenda

Pizza buffet provided to attendees at 5 pm, with technical talk to begin promptly at 5:10 pm.


Free parking available to attendees at NJIT parking garage across street from the ECE Building.  The talk will take place on the 2nd floor of the ECE Building in CR ECE202.