AKTU Detection & Estimation of Signals (HTAC601) Syllabus PDF – B.Tech Honors Degree in Advance Communication Technology

Course Objectives

1. The students will be able to apply various methods of signal estimation knowing the significance of each method.
2. The students will be able to decide which a good estimator for the given specifications is.
3. By applying suitable criterion, the students will be able to detect the signals with minimum errorsin the presence of noise. Course Outcomes:-
4. To understand the discrete time signals and systems
5. To analyze knowledge about various estimation techniques like parametric and non-parametric estimation techniques.
6. To able the gain knowledge for finding good estimators.
7. To analyze enough knowledge for detection of signal in noise
8. To understand the estimate the signals in the presence of noise.

Course Content

UNIT – I INTRODUCTION TO DISCRETE-TIME SIGNALS Simple signals, Fourier Transform of a discrete-time signal, Amplitude and phase spectrum, Frequency content and sampling rates, Transfer function, Frequency response. Review of probability, Random data, Generation of Pseudo-random noise, Filtered signals, Autocorrelation and power spectral density, Sampling band, Limited random signals.

UNIT – II MODERN (PARAMETRIC) SPECTRAL ESTIMATION:

Time series models, relationship between auto-correlation and the model parameters, AR Parameters by Yule-walker, Burg and Sequential estimation methods, selection of AR model order, MA and ARMA models for power spectrum estimator, Maximum entropy spectral estimator, Minimum variance spectral estimator.

UNIT – III DETECTION OF SIGNALS IN NOISE Minimum probability of Error Criterion – Neyman – Pearson criterion for Radar detection of constant and variable – amplitude signals – Matched filters – Optimum formulation – Detection of Random signals – Simple problems thereon with multi sample case UNIT – IV ESTIMATION OF SIGNALS IN NOISE Linear mean squared estimation- Nonlinear estimates- MAP and ML estimates- Maximum likelihood estimate of parameters of linear system- Simple problems on the area.

UNIT – V RECURSIVE LINEAR MEAN SQUARED ESTIMATION Estimation of a signal parameter – Estimation of time-varying signals – Kalman filtering – Filtering signals in noise – Treatment restricted to two variable case only – Simple problems

Text Books

1. Signal processing: Discrete Spectral analysis, Detection and Estimation, Mischa Schwartz and Leonard Shaw, Mc-Graw Hill.
2. H.L.Van Trees, Detection, Estimation and Modulation Theory, Wiley, New York, 1968.
3. Alan V. Oppenheim and Ronald W. Schaffer, Digital Signal Processing, PHI,3rd edition,2002.

Reference Books

1. Shanmugam and Breipohl, ‘Detection of signals in noise and estimation’, John Wiley & So Sons, New York, 1985.
2. Fundamentals of Statistical Signal Processing: Volume I Estimation Theory– Steven.M.Kay, Prentice Hall, USA, 1998.
3. Fundamentals of Statistical Signal Processing: Volume I Detection Theory– Steven.M.Kay, Prentice Hall, USA, 1998