Sonar Signal Processing (Artech House Acoustics Library)
This discussion of sonar signal processing bridges a number of related fields, including acoustic propagation in the medium, detection and estimation theory, filter theory, digital filtering, sensor array processing, spectral analysis, fast transforms and digital signal processing. The book begins with a discussion of the topics of analogue signalling conditioning, digital filtering, and the calculation of the discrete Fourier transform. Other topics discussed include analogue filters and analogue-to-digital conversion, finite impulse and infinite impulse response digital filters, and multirate processing techniques.
Why Read This Book
You will gain a rigorous, application-focused foundation in sonar digital signal processing that ties physical acoustics to practical algorithm design, so you can move from propagation and measurement to implementable detection and estimation systems. Nielsen balances theory (detection/estimation, statistical signal processing) with concrete DSP tools (digital filters, FFTs, multirate and array processing) useful for real sonar, underwater acoustics, and related sensing problems.
Who Will Benefit
Engineers and researchers with some signal-processing and math background who work on sonar, underwater acoustics, radar/sonar signal processing, or sensor-array systems and need a unified, practical reference linking physics to DSP algorithms.
Level: Advanced — Prerequisites: Undergraduate-level signals and systems (Fourier/DTFT, convolution), linear algebra, probability and random processes, calculus; familiarity with basic digital filtering and programming (MATLAB/C) is highly recommended.
Key Takeaways
- Understand acoustic propagation in water and how medium physics shapes sonar signal models and processing choices.
- Apply detection and estimation theory to design and analyze sonar detectors, matched filters, and likelihood-based estimators.
- Design and implement FIR and IIR digital filters, including practical considerations for analog-to-digital conversion and anti-aliasing.
- Implement FFT-based spectral analysis and fast transforms for sonar signal analysis and real-time processing.
- Use sensor array processing techniques (beamforming, DOA estimation, array gain) to improve detection and localization.
- Apply multirate and adaptive filtering approaches to improve performance in bandwidth-limited or nonstationary underwater environments.
Topics Covered
- 1. Introduction to Sonar Systems and Signal Models
- 2. Acoustic Propagation and Underwater Channel Characteristics
- 3. Analog Signal Conditioning and A/D Conversion for Sonar
- 4. Discrete-Time Signals and the Discrete Fourier Transform
- 5. Digital Filter Theory: FIR and IIR Design and Implementation
- 6. Multirate Signal Processing: Decimation, Interpolation, and Filter Banks
- 7. Spectral Analysis and Fast Fourier Transform Techniques
- 8. Detection and Estimation Theory Applied to Sonar
- 9. Matched Filtering and Correlation Receivers
- 10. Sensor Array Processing: Beamforming and Direction Finding
- 11. Adaptive Filtering and Space–Time Processing for Sonar
- 12. Practical System Considerations, Implementation Issues, and Case Studies
Languages, Platforms & Tools
How It Compares
Compared with Urick's Principles of Underwater Sound (which emphasizes propagation and empirical acoustics), Nielsen adds a stronger DSP and detection/estimation treatment; for statistical detection theory complement, pair it with Van Trees' or Kay's texts on detection/estimation for deeper theoretical foundations.
