Imaging with Synthetic Aperture Radar (Engineering Sciences: Electrical Engineering)
Describing a field that has been transformed by the recent availability of data from a new generation of space and airborne systems, the authors offer a synthetic geometrical approach to the description of synthetic aperture radar, one that addresses physicists, radar specialists, as well as experts in image processing.
Why Read This Book
You will gain a clear, geometry-driven understanding of how modern spaceborne and airborne SAR systems form images and what that implies for signal processing and image analysis. The book connects radar physics to practical DSP and imaging algorithms, so you can move from theory to implementation and correctly interpret real SAR data.
Who Will Benefit
Advanced engineers, remote-sensing scientists, and graduate students with DSP or radar backgrounds who need to design, implement, or interpret SAR imaging and interferometric workflows.
Level: Advanced — Prerequisites: Undergraduate-level linear systems and signals, Fourier transforms and sampling theory, basic radar/EM concepts, and familiarity with digital signal processing (filters, FFTs) and probability/statistics.
Key Takeaways
- Derive and apply the geometric and signal models that underlie SAR image formation and resolution.
- Implement and compare central image formation algorithms (range-Doppler, backprojection, chirp-scaling/Omega-K).
- Design pulse-compression and digital filtering strategies for SAR, including practical FFT-based implementations.
- Apply interferometric and polarimetric processing methods for topography, deformation mapping, and target characterization.
- Analyze and mitigate speckle and noise using statistical signal-processing and image-domain techniques.
- Assess system trade-offs (bandwidth, aperture, motion errors, ambiguities) and their impact on spectral analysis and image quality.
Topics Covered
- 1. Introduction to Synthetic Aperture Radar and System Overview
- 2. Electromagnetic and Geometrical Foundations of SAR
- 3. SAR Signal Model: Range, Doppler, and Sampling
- 4. Pulse Compression and Digital Filter Design for SAR
- 5. Range-Doppler and Wavenumber (Omega-K) Imaging Algorithms
- 6. Backprojection and Time-Domain Image Formation
- 7. Motion Compensation, Autofocus, and Platform Errors
- 8. Interferometric SAR (InSAR): Geometry, Processing, and Applications
- 9. Polarimetric SAR and Target Characterization
- 10. Speckle, Statistical Signal Processing, and Image Enhancement
- 11. Spectral Analysis, FFT Implementations, and Practical Considerations
- 12. Advanced Topics: Multichannel SAR, Wavelets, and Adaptive Filtering
- 13. Applications: Topography, Glacier/Ocean Monitoring, and Change Detection
- Appendices: Mathematical Tools (Fourier transforms, linear systems, probability) and Data Examples
Languages, Platforms & Tools
How It Compares
Compared with the classic system- and signal-processing focus of Curlander & McDonough, Massonnet emphasizes a synthetic geometrical approach that links SAR physics directly to image processing and interferometry applications.
