Using Coupled Multilinear Rank-(L, L, 1) Block Term Decomposition in Multi-Static-Multi-Pulse MIMO Radar to Localize Targets

Block-Term Tensor Decomposition in Array Signalprocessing

“…In [16] and earlier related works including [17,18,19], BTD is shown to be the natural modeling choice for the output of an array with signals impinging through multiple paths and being subject to oversampling and/or intersymbol interference (ISI) 1 . Rank-(M, N, •) decomposition [13], also known as type-2 BTD (i.e., with Tucker-2 blocks), and coupled LL1 decomposition were used in [20] and [21] to perform target localization in multi-pulse, multi-array MIMO radar, with and without training waveforms, respectively. [21] was recently extended to near-field targets in [22].…”

“…Rank-(M, N, •) decomposition [13], also known as type-2 BTD (i.e., with Tucker-2 blocks), and coupled LL1 decomposition were used in [20] and [21] to perform target localization in multi-pulse, multi-array MIMO radar, with and without training waveforms, respectively. [21] was recently extended to near-field targets in [22]. The direction-finding (DF) problem in L-shaped electromagnetic vector sensor arrays with timevarying polarization state (i.e., partial or incomplete polarization) was also solved with the aid of type-2 BTD modeling in [23,24].…”

$(L_r,L_r,1)$-Decompositions, Sparse Component Analysis, and the Blind Separation of Sums of Exponentials

“…The so-called pL r , L r , 1qdecompositions are special kind of block-term decomposition [21,22], wherein a thirdorder tensor T P C IˆJˆK is expanded in the form h ij m k . The decomposition (1.1) has found its use in various signal processing applications including wireless communication [20], chemometrics [11], target localization in radar imaging [54], and blind source separation [23,24,25]. Unlike for canonical polyadic decompositions (CPDs) wherein each term has unit rank, pL r , L r , 1qdecompositions have wider applicability as they allow for more general terms.…”