Reducing the Number of Elements in the Synthesis of Shaped-Beam Patterns by the Forward-Backward Matrix Pencil Method
By Yanhui Liu, Qing Huo Liu, Z. Nie. IEEE Transactions on Antennas and Propagation, 2010
150 citations recorded by the source corpus.
Subfields: Aerospace Engineering, Electrical and Electronic Engineering
View Paper: https://www.semanticscholar.org/paper/a3229c1ed2b8161e45448b232f203ae79db4d10f
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In Aerospace Engineering
In Electrical and Electronic Engineering
Citations in the corpus
- A NEW METHOD FOR THE SYNTHESIS OF NON- UNIFORM LINEAR ARRAYS WITH SHAPED POWER PATTERNS (2010, unknown): “Then the FBMPM-based synthesis method organizes the pattern data into a Hankel-Toeplitz matrix [15] where Here L is called the pencil parameter.”
- Maximally Sparse Arrays Via Sequential Convex Optimizations (2012, background): “In the proposed synthesis approach, differently from [5], [6], and [8]–[10], only the upper bound of the power pattern is assigned (and not a reference field, in amplitude and phase), thus allowing to determine the minimum number of required sensors independently on the particular reference field.”
- Synthesis of Nonuniformly Spaced Linear Arrays With Frequency-Invariant Patterns by the Generalized Matrix Pencil Methods (2015, methodology): “rank matrix approximation technique, as did in the original MPM-based synthesis methods [22], [23].”
- Synthesis of Sparse Arrays With Focused or Shaped Beampattern via Sequential Convex Optimizations (2012, methodology): “Matrix pencil methods (MPM) have lately been efficiently applied to reconstruct focused and shaped beampatterns while reducing the number of the array elements [13]–[15].”
- Reducing the Number of Elements in Multiple-Pattern Linear Arrays by the Extended Matrix Pencil Methods (2014, methodology): “where is appropriate for the usual case [20].”
- Sparse Array Beampattern Synthesis via Alternating Direction Method of Multipliers (2018, methodology): “Other design techniques include spatial tapering [10], [11], matrix pencil [12], [13], and stochastic optimization such as particle swarm [14], genetic algorithm [15], ant colony [16], and simulated annealing [17], [18].”