Spatial Signal Processing  046743
Will not be given the year



Lecture 
Exercise 
Laboratory 
Project or Seminar 
House Work 
Weekly Hours 
2 
1 


8 

Determination of the grade according to progress during the semester and a final examination.
Prerequisites:
 
(
  Intro. to Digital Signal Processing 
044198
 
  
and
 Random Signals 
044202
 ) 
A
rrays and Spatial Filters, Beam Patterns, Uniform Linear Arrays, Array Performance Measures. Optimum Waveform Estimation (Beamforming), Minimum Variance Distortionless Response (Mvdr), Linearly Constrained Minimum Variance (Lcmv) Generalized Sidelobe Cancellers (Gsc), Maximum Snr, Broadband Beamformers. Adaptive Noise Cancellation. Source Separation and Signal Dereverberation. Source Localization, Direction of Arrival (Doa) and Time Difference of Arrival (Tdoa) Estimation.
Learning Outcomes
A
t the End of the Course the Student Will Be Able to
1. Design An Optimum Beamformer for Spatial Filtering in Sensor Arrays.
2. Enhance and Extract Signals Received by Sensor Arrays.
3. Design An Lcmv Filter for Noise Reduction and Dereverberation.
4. Implement An Algorithm for Adaptive Noise Cancellation.
5. Implement An Algorithm for Source Separation and Signal Dereverberation.
6. Estimate Direction of Arrival and Time Difference of Arrival.
TextbooksPublished  Publisher  Authors  Book 

2002  john wiley and sons,inc  h.l.van trees  optimum array processing: part 4 of detection estimation,and modulation theory 
2008  springer  j.benesty j.benesty  microphone array signal processing 
1993  prenticehall,inc  d.h.johnson d.h.johnson  array signal processing: concepts and techniques 
Created in 21/11/2017 Time 06:16:03