Detection Theory: Applications and Digital Signal Processing
Continuous Signals and Systems with MATLAB is the first undergraduate text fully focused on continuous systems. It presents all of the material needed to master the subject and its related MATLAB problem-solving techniques. The authors cover all of the traditional topics and include chapters on system design, state-space techniques, linearizing nonlinear systems, and the design and analysis of analog filters. They also discuss the five representations of continuous systems and explain how to go from one representation to another.
Why Read This Book
You should read this book if you need a practical bridge between statistical detection theory and real DSP implementations: it shows how likelihood-ratio tests, matched filters, and performance metrics map into algorithms you can implement and test (MATLAB examples included). It emphasizes application-driven methods used in radar and communications so you can move from theory to working detectors quickly.
Who Will Benefit
Advanced DSP engineers, radar and communications practitioners, and graduate students who design or implement signal detectors and need both the theory and practical DSP recipes.
Level: Advanced — Prerequisites: Probability and random processes, basic statistical inference, linear systems and signal processing fundamentals, and familiarity with MATLAB for following examples.
Key Takeaways
- Formulate detection problems using likelihood-ratio and Bayesian frameworks and derive optimal detectors for standard models.
- Design and implement matched-filter and correlation detectors for deterministic and random signals in noise.
- Evaluate detector performance using ROC curves, probability of detection/false alarm, and SNR measures.
- Apply generalized likelihood-ratio tests (GLRT) and practical approximations when signal parameters are unknown.
- Implement spectral and FFT-based detection methods and understand windowing/estimation issues affecting performance.
- Adapt detector designs for practical scenarios (CFAR, nonstationary noise, real-time DSP constraints) using MATLAB prototyping.
Topics Covered
- 1. Introduction to Detection Theory and DSP Perspective
- 2. Probability Foundations and Gaussian Models
- 3. Performance Measures: ROC, Pd, Pfa, SNR
- 4. Detection of Deterministic Signals in Gaussian Noise
- 5. Matched Filters and Correlation Receivers
- 6. Detection of Stochastic Signals and Spectral Methods
- 7. Generalized Likelihood Ratio Tests and Parameter Estimation
- 8. FFT-based and Frequency-Domain Detection Techniques
- 9. Adaptive Detection, CFAR, and Nonstationary Noise
- 10. Practical DSP Implementation and MATLAB Examples
- 11. Applications to Radar and Communication Receivers
- 12. Appendices: Useful Transforms, Tables, and Implementation Notes
Languages, Platforms & Tools
How It Compares
More applied and DSP-focused than Van Trees' multi-volume theoretical treatment and more implementation-oriented than Kay's Detection Theory chapters — Hippenstiel emphasizes practical MATLAB/DSP realizations for radar and comms use-cases.
