Why Read This Book

You should read this book to gain a rigorous, unified foundation in detection and estimation theory that underpins modern radar, sonar and communication signal processing. It blends deep theoretical development with worked examples and problems so you can both understand proofs and apply the methods to real detection/estimation problems.

Who Will Benefit

Graduate students, researchers, and practicing engineers in radar, communications, and statistical signal processing who need a rigorous theoretical grounding and reference.

Level: Advanced — Prerequisites: Solid probability and random processes, multivariable calculus, linear algebra, and a basic background in signals and systems or DSP.

Key Takeaways

• Apply Neyman-Pearson and likelihood-ratio principles to construct optimal detectors for simple and composite hypotheses.
• Derive and implement matched filters and optimum detection strategies for signals in Gaussian noise.
• Formulate and compute parameter estimators (MLE, Bayesian estimators) and assess estimator performance using the Cramér-Rao bound.
• Analyze detector and estimator performance in terms of error probabilities, receiver operating characteristics, and bounds.
• Use Bayesian decision theory to incorporate priors and cost functions into practical decision rules.
• Extend detection/estimation methods to modulation and communication system analysis and performance evaluation.

Topics Covered

1. Preface and historical context
2. Probability and random processes — preliminaries
3. Fundamentals of detection theory and hypothesis testing
4. Likelihood-ratio tests and the Neyman-Pearson criterion
5. Detection of deterministic signals in Gaussian noise — matched filters
6. Composite hypotheses and detection with unknown parameters
7. Bayesian detection and decision theory
8. Introduction to estimation theory — unbiasedness, consistency
9. Maximum likelihood and Bayesian parameter estimation
10. Cramér-Rao bound, efficiency, and performance bounds
11. Multivariate parameter estimation and Fisher information
12. Applications to communication and radar problems; examples and exercises

How It Compares

More comprehensive and classical in scope than S. M. Kay's more concise, practitioner-focused volumes; complements H. Vincent Poor's introductory book by providing deeper theoretical breadth and historical treatment.