SIAM Journal on Matrix Analysis and Applications
SIAM Journal on Matrix Analysis and Applications
Multidimensional rank reduction estimator for parametric MIMO channel models
EURASIP Journal on Applied Signal Processing
Multitarget identification and localization using bistatic MIMO radar systems
EURASIP Journal on Advances in Signal Processing
Decompositions of a Higher-Order Tensor in Block Terms—Part I: Lemmas for Partitioned Matrices
SIAM Journal on Matrix Analysis and Applications
Decompositions of a Higher-Order Tensor in Block Terms—Part II: Definitions and Uniqueness
SIAM Journal on Matrix Analysis and Applications
SIAM Journal on Matrix Analysis and Applications
Enhanced Line Search: A Novel Method to Accelerate PARAFAC
SIAM Journal on Matrix Analysis and Applications
A PARAFAC-based technique for detection and localization of multiple targets in a MIMO radar system
ICASSP '09 Proceedings of the 2009 IEEE International Conference on Acoustics, Speech and Signal Processing
A comparison of algorithms for fitting the PARAFAC model
Computational Statistics & Data Analysis
Adaptive algorithms to track the PARAFAC decomposition of a third-order tensor
IEEE Transactions on Signal Processing
Tensor Decompositions and Applications
SIAM Review
Blind multipath MIMO channel parameter estimation using the Parafac decomposition
ICC'09 Proceedings of the 2009 IEEE international conference on Communications
Almost sure identifiability of constant modulus multidimensional harmonic retrieval
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing - Part II
Blind high-resolution localization and tracking of multiplefrequency hopped signals
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing
A Block Component Model-Based Blind DS-CDMA Receiver
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing
Parallel factor analysis in sensor array processing
IEEE Transactions on Signal Processing
Efficient mixed-spectrum estimation with applications to targetfeature extraction
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing
MIMO Radar Space–Time Adaptive Processing Using Prolate Spheroidal Wave Functions
IEEE Transactions on Signal Processing
Multidimensional Frequency Estimation With Finite Snapshots in the Presence of Identical Frequencies
IEEE Transactions on Signal Processing
Almost-sure identifiability of multidimensional harmonic retrieval
IEEE Transactions on Signal Processing
| Hi-index | 35.68 |
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.