2019
DOI: 10.1109/tap.2019.2899850
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Monopulse Beam Synthesis Using a Sparse Single Layer of Weights

Abstract: A conventional monopulse radar system uses three beams; sum beam, elevation difference beam and azimuth difference beam, which require different layers of weights to synthesize each beam independently. Since the multi-layer structure increases hardware complexity, many simplified structures based on a single layer of weights have been suggested. In this work, we introduce a new technique for finding disjoint and fully covering sets of weight vectors, each of which constitutes a sparse subarray, forming a singl… Show more

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Cited by 9 publications
(2 citation statements)
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“…However, for the dynamic subarray case, the situation is more complicated. The synthesis of the sum or difference beam under the dynamic subarray cannot utilize a simple closed-form analytic solution and requires a complex numerical computation [63]- [65]. However, assuming such a numerical method is available for providing sum and difference beams satisfying both (20) and (21), the proposed AoA error estimation can be applied to the dynamic subarray case in a straightforward manner.…”
Section: B: Monopulse Ratio Based Aoa Error Estimatormentioning
confidence: 99%
“…However, for the dynamic subarray case, the situation is more complicated. The synthesis of the sum or difference beam under the dynamic subarray cannot utilize a simple closed-form analytic solution and requires a complex numerical computation [63]- [65]. However, assuming such a numerical method is available for providing sum and difference beams satisfying both (20) and (21), the proposed AoA error estimation can be applied to the dynamic subarray case in a straightforward manner.…”
Section: B: Monopulse Ratio Based Aoa Error Estimatormentioning
confidence: 99%
“…Each weight vector set forms a sparse subarray to form a single beam. Our algorithm decomposes the original nonconvex optimization problem into the problem of finding disjoint weight vectors [26]. Morabito proposed a new synthetic one-dimensional reconfigurable sparse array method, which can generate summation and difference power patterns.…”
Section: Introductionmentioning
confidence: 99%