2015
DOI: 10.1109/lawp.2014.2354334
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Transmit and Receive Array Gain-Phase Error Estimation in Bistatic MIMO Radar

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Cited by 34 publications
(25 citation statements)
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“…. x M are the position errors of the subarray X; the full-rank matrix T is degraded to a constant t, and the signal subspace matrix E is degraded to a (M + 1) dimension vector e. Then, the subspaces corresponding to the two subarrays satisfy: e = e x e y = at Fae jϕ t (16) When Eq. (15) is taken into matrix D in step (d), the matrix D is degraded to a constant g, in which:…”
Section: Formulation Of Design Problemmentioning
confidence: 99%
See 1 more Smart Citation
“…. x M are the position errors of the subarray X; the full-rank matrix T is degraded to a constant t, and the signal subspace matrix E is degraded to a (M + 1) dimension vector e. Then, the subspaces corresponding to the two subarrays satisfy: e = e x e y = at Fae jϕ t (16) When Eq. (15) is taken into matrix D in step (d), the matrix D is degraded to a constant g, in which:…”
Section: Formulation Of Design Problemmentioning
confidence: 99%
“…The rotation invariance of the subarray generated by the displacement invariance of the subarray is used to solve the direction of the signal according to the rotation phase between the subfields of the subarray. Compared with other high-resolution DOA estimation algorithms, this algorithm does not need angle search, and the estimation result can be directly calculated [14][15][16].…”
Section: Introductionmentioning
confidence: 99%
“…VBI 28 could be used to find a tractable distribution qðΩÞ that closely approximates the true posterior distribution pðΩjy; φÞ by minimizing the Kullback-Leibler divergence (KLD) between them. A structured mean field approximation over pðΩjy; φÞ is further assumed as E Q -T A R G E T ; t e m p : i n t r a l i n k -; e 0 1 1 ; 6 3 ; 7 3 0 qðΩÞ ¼ qðβÞqðαÞqðηÞqðα 0 Þ: (11) VBI is carried out using VMP 24 in this paper. VMP is an iterative scheme that uses a message passing procedure on a graphical model and attempts to compute the auxiliary PDF.…”
Section: Variational Message Passingmentioning
confidence: 99%
“…5,6 To compensate the phase error, several eigenstructure-based methods are proposed. [7][8][9][10][11] These methods are less sensitive to phase error but lack adaptation to demanding scenarios with low signal-to-noise ratio (SNR), limited snapshots, and spatially adjacent sources. 12 Recently, sparse recovery and compressive sensing 13 are introduced into signal processing by exploiting the sparsity.…”
Section: Introductionmentioning
confidence: 99%
“…In 2015, the authors in [18] proposed the sparse auto-calibration method to compensate the gain-phase error in radar coincidence imaging. In the same year, an Estimation of Signal Parameters via Rotational Invariance Techniques (ESPRIT)-based method was presented to estimate the gain-phase errors [19]. Furthermore, the problem of direction-of-arrival (DOA) estimation for monostatic MIMO radar with gain-phase errors was addressed [20].…”
Section: Introductionmentioning
confidence: 99%