Digital Processing of Synthetic Aperture Radar Data: Algorithms and Implementation (Artech House Remote Sensing Library)
Synthetic Aperture Radar (SAR) is of major interest to radar professionals because it allows them to obtain high-resolution images with unsurpassed clarity from satellites that take pictures of the earth's surface in all weather conditions. This cutting-edge resource offers complete "how to" guidance on digital processing of synthetic aperture radar (SAR) data. Professionals discover precisely how this radar system works and gain an in-depth understanding of the properties of SAR data. The book explains how digital computers are used to form the focused image and provides practitioners with state-of-the-art processing algorithms that they can use for their projects. Written from a signal processing point of view, this authoritative volume can be fully understood by professionals and students with a general electrical engineering background.
Why Read This Book
You will learn how to turn raw SAR echoes into focused, high-resolution imagery using practical, state-of-the-art algorithms and implementation guidance; the book emphasizes signal-processing methods you can implement and tune for real systems. It balances theory and hands‑on detail (including code on the CD-ROM) so you can move from mathematical models to working image-formation pipelines and performance tradeoffs.
Who Will Benefit
Radar and remote‑sensing engineers, graduate students, and signal-processing practitioners who need to design or implement SAR image‑formation, autofocus, and related processing chains for airborne or spaceborne systems.
Level: Advanced — Prerequisites: Solid background in digital signal processing (Fourier transforms, sampling, digital filtering), linear systems, basic radar principles (pulse compression, PRF), and familiarity with MATLAB or a similar scientific computing environment.
Key Takeaways
- Implement core SAR image‑formation algorithms such as range‑Doppler, chirp‑scaling, and omega‑k (2D FFT) to produce focused images from raw SAR data.
- Design and apply matched filters and pulse‑compression techniques, and optimize digital filter implementations for SAR waveforms.
- Apply motion compensation and autofocus methods to correct platform motion errors and improve image coherence and resolution.
- Use FFT-based spectral analysis, interpolation, and resampling methods effectively in 2‑D processing chains and understand their computational tradeoffs.
- Mitigate speckle and control radiometric and geometric image quality using multilooking, calibration, and basic speckle‑reduction strategies.
- Analyze sampling, aliasing, and resolution constraints for SAR systems and map those constraints into implementation choices.
Topics Covered
- Introduction to Synthetic Aperture Radar and the SAR Processing Problem
- Geometry, Signal Model, and Data Acquisition
- Matched Filtering and Range Compression
- Azimuth Processing and the Range‑Doppler Algorithm
- Chirp‑Scaling and Omega‑k (2‑D FFT) Algorithms
- Time‑Domain/Backprojection Imaging and Spotlight SAR
- Motion Compensation, Autofocus, and Phase Errors
- Digital Filters, Interpolation, and FFT Implementation Issues
- Resolution, Ambiguity, Sampling, and Radiometry
- Speckle, Multilooking, and Basic Image Enhancement
- Practical Implementation, Computational Costs, and Real‑Data Examples
- Appendices/CD‑ROM: Code, Test Data, and Algorithmic Utilities
Languages, Platforms & Tools
How It Compares
Covers similar practical, implementation‑oriented ground as Mehrdad Soumekh's MATLAB‑heavy SAR text but offers a more algorithmic signal‑processing perspective and more implementation heuristics; it complements the classic systems overview in Curlander & McDonough by focusing on digital processing and software realization.
