EE4715 Array processing

Topics: Array processing techniques for signal separation and parameter estimation

In this course we discuss array processing techniques for signal separation and parameter estimation, using arrays of sensors. After a review/introduction of the necessary linear algebra tools we will start with deriving the signal processing model for narrowband applications, followed by the wideband extension, and apply these to several applications among which array processing for wireless communication, audio and speech processing, biomedical signal processing and astronomy.

Course contents

Signal processing models for narrowband and wideband array processing, elementary beamforming concepts (spatial filtering), tools from linear algebra: QR, SVD, eigenvalue decompositions, projections and GEVD. Elementary beamformers/receivers: the matched filter, the Wiener filter, MVDR, LCMV, etc. Estimation of angles and delays using ESPRIT,  factor analysis. Wideband signals: microphone arrays.

Teachers Geert Leus

Signal processing for communications, with applications to underwater communications, cognitive radio, and multiple-input multiple-output (MIMO) systems. Signal processing for (compressive) sensing with applications to ultrasound imaging and radar. Distributed signal processing. Graph signal processing. Richard Hendriks

Audio signal processing, signal processing for hearing aids, biomedical signal processing Alle-Jan van der Veen

Array signal processing; Signal processing for communications

Last modified: 2022-06-19


Credits: 5 EC
Period: 0/0/0/4
Contact: Richard Hendriks