References & Further Reading

References

1. G. Caire, On the Illumination and Sensing Model for RF Imaging, 2026

   The primary reference for the forward model framework used throughout this chapter. Derives the unified illumination model from diffraction tomography, the wavenumber-domain analysis, and the discretized linear system $\ntn{img_model} = \ntn{sens}\ntn{refl} + \ntn{noise}$.

2. A. J. Devaney, Mathematical Foundations of Imaging, Tomography and Wavefield Inversion, Cambridge University Press, 2012

   Rigorous treatment of inverse scattering, diffraction tomography, and scene representations for wave-based imaging. Sections s01 (scene representations), s04 (near-field), and s05 (Born breakdown) draw extensively on Devaney's framework.

3. C. A. Balanis, Advanced Engineering Electromagnetics, Wiley, 2nd edition, 2012

   Standard reference for electromagnetic theory including ray tracing (GTD/UTD), physical optics, and full-wave methods. Section s02 (deterministic channel models) follows this framework.

4. A. F. Molisch, Wireless Communications, Wiley, 2nd edition, 2012

   Comprehensive treatment of stochastic channel models. Section s03 contrasts the telecom approach with imaging requirements.

5. M. A. Richards, J. A. Scheer, and W. A. Holm, Principles of Modern Radar: Basic Principles, SciTech Publishing, 2014

   Covers Swerling models, clutter statistics, and calibration. The primary reference for Section s03 (stochastic scattering) and the detection/clutter exercises.

6. J. W. Goodman, Speckle Phenomena in Optics: Theory and Applications, Roberts and Company, 2007

   Definitive treatment of speckle statistics (Rayleigh, Rician, K-distribution). Section s03 (Theorem on Rayleigh speckle) and the speckle reduction engineering note follow Goodman.

7. M. G. Amin, Through-the-Wall Radar Imaging, CRC Press, 2017

   Comprehensive treatment of through-wall radar, multipath ghost modeling, and wall compensation. Sections s02 (through-wall model and multipath) and the related exercises draw on this reference.

8. Y. Chi, L. L. Scharf, and A. Pezeshki, Sensitivity to Basis Mismatch in Compressed Sensing, 2011

   Analyzes how basis mismatch degrades compressed sensing recovery. The gridding error analysis in Section s05 and the mismatch-robustness theorem follow this paper.

9. W. C. Chew and Y. M. Wang, Reconstruction of Two-Dimensional Permittivity Distribution Using the Distorted Born Iterative Method, 1990

   Introduces the DBIM for multiple-scattering scenarios. Referenced in Section s05 for Born approximation breakdown and alternatives.

10. T. S. Rappaport, R. W. Heath Jr., R. C. Daniels, and J. N. Murdock, Millimeter Wave Wireless Communications, Prentice Hall, 2015

    Covers mmWave channel modeling including ray tracing. Relevant to the near-field examples and mmWave imaging scenarios.

11. M. I. Skolnik, Radar Handbook, McGraw-Hill, 3rd edition, 2008

    Comprehensive radar reference covering detection, clutter, and calibration. Provides background for the practical effects discussed throughout this chapter.

12. J. Ward, Space-Time Adaptive Processing for Airborne Radar, MIT Lincoln Laboratory Technical Report 1015, 1994

    Foundational treatment of STAP for clutter mitigation. Referenced for the clutter exercises.

Further Reading

• Differentiable ray tracing for RF imaging

  Sionna RT (NVIDIA): GPU-accelerated, differentiable ray tracing for wireless channel modeling and sensing geometry optimization

  Modern tools for constructing deterministic channel models with gradient support, enabling joint optimization of sensing geometry and reconstruction algorithms.

• Compressed sensing with basis mismatch

  Y. Chi et al., Sensitivity to Basis Mismatch in Compressed Sensing, IEEE Trans. SP, 2011

  Rigorous analysis of how off-grid targets degrade CS recovery, with bounds on reconstruction error as a function of grid spacing.

• Inverse scattering beyond Born

  W. C. Chew and Y. M. Wang, DBIM, IEEE Trans. MI, 1990

  Extends the Born-based forward model to multiple-scattering scenarios via iterative refinement of the background field.

• Speckle statistics and reduction

  J. W. Goodman, Speckle Phenomena in Optics, 2007

  Definitive reference for understanding and mitigating speckle in coherent imaging systems, with direct application to SAR and MIMO radar imaging.