References & Further Reading

References

  1. J. Li and P. Stoica, MIMO Radar with Colocated Antennas, 2007

    Foundational paper establishing the co-located MIMO radar signal model, virtual aperture concept, and waveform diversity. Primary source for Sections 11.1 and 11.4.

  2. A. M. Haimovich, R. S. Blum, and L. J. Cimini, MIMO Radar with Widely Separated Antennas, 2008

    Extends MIMO radar to the distributed case with spatial diversity. Source for the detection diversity analysis in Section 11.2.

  3. E. Fishler, A. Haimovich, R. Blum, D. Chizhik, L. Cimini, and R. Valenzuela, MIMO Radar: An Idea Whose Time Has Come, 2004

    One of the earliest papers on MIMO radar, introducing the statistical spatial diversity concept for detection.

  4. A. Hassanien and S. A. Vorobyov, Phased-MIMO Radar: A Tradeoff Between Phased-Array and MIMO Radars, 2010

    Introduces the phased-MIMO concept: partitioning the transmit array into sub-arrays for a tuneable coherent-gain vs. waveform-diversity trade-off. Key reference for Section 11.2.

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

    Unifies diffraction-tomography and MIMO radar sensing models. Establishes the Kronecker and Khatri-Rao structure of the MIMO sensing matrix. Primary source for Section 11.4.

  6. N. J. Willis, Bistatic Radar, SciTech Publishing, 2nd ed., 2005

    Comprehensive reference on bistatic radar geometry, isorange ellipses, and bistatic range resolution.

  7. S. Sun, A. P. Petropulu, and H. V. Poor, MIMO Radar for Advanced Driver-Assistance Systems and Autonomous Driving: Advantages and Challenges, 2020

    Practical MIMO radar design for automotive imaging, including TDM-MIMO and array design considerations.

  8. M. Wang, W. Li, and Y. D. Zhang, Sparse Array Design for MIMO Radar Imaging, 2018

    Sparse and minimum-redundancy MIMO array design for maximising imaging resolution while controlling conditioning.

  9. B. Friedlander, On the Relationship Between MIMO and SIMO Radars, 2012

    Clarifies conditions under which MIMO radar outperforms phased-array radar for detection and estimation.

  10. M. Manzoni, A. Monti Guarnieri, and S. Tebaldini, Wavefield Networked Sensing: Principles, Algorithms, and Applications, 2025

    Multi-AP imaging using diffraction tomography per AP. Connects the multi-view geometry of Section 11.3 to networked sensing systems.

  11. S. Mandelli et al., Spatial Sampling Theorems for MIMO Radar, 2025

    Spatial sampling theorems and Dirichlet kernels for MIMO arrays. Uses notation familiar to communications researchers.

  12. P. Rocca, L. Poli, and A. Massa, Synthesis of Thinned Arrays for MIMO Radar Imaging, 2016

    Array thinning and optimisation for MIMO radar, balancing resolution and conditioning.

Further Reading

For readers who want to go deeper into specific topics from this chapter.

  • MIMO radar waveform design

    B. Tang, J. Tang, and Y. Peng, 'MIMO radar waveform design in colored noise based on information theory,' IEEE Trans. Signal Processing, vol. 58, no. 9, 2010

    Information-theoretic waveform design that maximises mutual information between the transmitted signal and the scene.

  • Compressive MIMO radar

    Y. Yu, A. P. Petropulu, and H. V. Poor, 'MIMO radar using compressive sampling,' IEEE J. Selected Topics Signal Processing, vol. 4, no. 1, 2010

    Combines MIMO radar with compressed sensing, enabling sub-Nyquist sampling while preserving imaging performance.

  • Coprime and nested array design

    P. Pal and P. P. Vaidyanathan, 'Nested arrays: A novel approach to array processing with enhanced degrees of freedom,' IEEE Trans. Signal Processing, vol. 58, no. 8, 2010

    Extends the virtual array concept to coprime and nested configurations that achieve more unique virtual positions than standard MIMO ULAs.

  • Bistatic radar fundamentals

    N. J. Willis, 'Bistatic Radar,' SciTech Publishing, 2nd edition, 2005 (Chapters 2--4)

    Comprehensive treatment of bistatic geometry, isorange contours, and resolution analysis.

  • NUFFT for non-uniform k-space

    L. Greengard and J. Lee, 'Accelerating the Nonuniform Fast Fourier Transform,' SIAM Review, vol. 46, no. 3, 2004

    The algorithmic foundation for efficient matrix-vector products with non-Kronecker sensing matrices.

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