Tensor Algebra and Multidimensional Harmonic Retrieval in Signal Processing for MIMO Radar
By Dimitri Nion, N. Sidiropoulos. IEEE Transactions on Signal Processing, 2010
323 citations recorded by the source corpus.
Detection and estimation problems in multiple-input multiple-output (MIMO) radar have recently drawn considerable interest in the signal processing community. Radar has long been a staple of signal processing, and MIMO radar presents challenges and opportunities in adapting classical radar imaging tools and developing new ones. Our aim in this article is to showcase the potential of tensor algebra and multidimensional harmonic retrieval (HR) in signal processing for MIMO radar. Tensor algebra and multidimensional HR are relatively mature topics, albeit still on the fringes of signal processing research. We show they are in fact central for target localization in a variety of pertinent MIMO radar scenarios. Tensor algebra naturally comes into play when the coherent processing interval comprises multiple pulses, or multiple transmit and receive subarrays are used (multistatic configuration). Multidimensional harmonic structure emerges for far-field uniform linear transmit/receive array configurations, also taking into account Doppler shift; and hybrid models arise in-between. This viewpoint opens the door for the application and further development of powerful algorithms and identifiability results for MIMO radar. Compared to the classical radar-imaging-based methods such as Capon or MUSIC, these algebraic techniques yield improved performance, especially for closely spaced targets, at modest complexity.
Subfields: Aerospace Engineering, Signal Processing
View Paper: https://www.semanticscholar.org/paper/c9ea1998d088611e61d6ec18b674eb045b6948af
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In Aerospace Engineering
- Kai Wu
- Senior Member Ieee Xiaojing Huang
- S. M. I. J. Andrew Zhang
- F. I. Y. Jay Guo
- Ieee Shanzhi Chen Fellow
- Fellow Ieee Jinhong Yuan
- Md. Lushanur Rahman
- Shan-zhi Chen
Citations in the corpus
- An Overview of Signal Processing Techniques for Joint Communication and Radar Sensing (2021, unknown): “More details of such techniques for JCR can be referred to [24], [37]–[40].”
- Enabling Joint Communication and Radar Sensing in Mobile Networks—A Survey (2020, methodology): “Tensor-based algorithms [180], [181] High-order formulation using the Tensor tools such as 3D Tensor CS simplifies computational complexity and provides capability in resolving multipath with repeated parameter values.”