CRL 704 Sensor Array Signal Processing
Representation of Space-Time Signals(Coordinate systems; propagating waves; wave number-frequency space;random fields; noise assumptions.) signal Modeling and Optimal Filters(Auto-regressive (AR), Moving average (MA), ARMA models; Autocorrelation and power spectral density (PSD) of random processes; linear minimum mean square and linear least squares error estimator; solution of normal equations; optimum filter; matched filters.) Adaptive Filter Theory (Motivation and applications; method of steepest descent; least mean squares adaptive filters; recursive least squares adaptive filters; Convergence issues and performance analysis.) Power Spectrum Estimation (Nonparametric methods; Estimation of autocorrelation function and PSD using periodogram; Blackman-Tukey and Welch-Barlett methods; Parametric methods : Model order selection; PSD estimation using rational spectral models; MUSIC ESPRIT).Signal Shaping for Transmission (Representation of band pass signals; band pass sampling theorem; Complex Envelope; Ambiguity function and its properties; Considerations in signal shaping.)
Array Processing (Array signal modeling; sensor array; geometries; spatial; sampling; beam forming- spatial and space-time filtering; array aperture; delay and sum beam forming; filter and sum beam forming; frequency domain beam forming; optimum beam forming: MVDR beam former, Generalized sidelobe canceller; Adaptive beam forming).
Back to Courses