2022 IEEE International Ultrasonics Symposium (IUS) 2022
DOI: 10.1109/ius54386.2022.9958020
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Grating Lobe Suppression Through Novel, Sparse Laser Induced Phased Array Design

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Cited by 4 publications
(4 citation statements)
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“…In the realisation of the SMC presented in this paper, highly sparse equidistant linear LIPAs were utilised during stage 1, the scatterer detection stage, however other sparse LIPA designs have been demonstrated (e.g. random arrays, Vernier) that are able to increase the array imaging ability with reduced number of array elements [6]. These designs could lead to the scatterer detection stage being able to locate the ROI earlier, further improving the speed of this method.…”
Section: Discussionmentioning
confidence: 99%
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“…In the realisation of the SMC presented in this paper, highly sparse equidistant linear LIPAs were utilised during stage 1, the scatterer detection stage, however other sparse LIPA designs have been demonstrated (e.g. random arrays, Vernier) that are able to increase the array imaging ability with reduced number of array elements [6]. These designs could lead to the scatterer detection stage being able to locate the ROI earlier, further improving the speed of this method.…”
Section: Discussionmentioning
confidence: 99%
“…Existing approaches include those that address sparsity based on: a) transducer phased array design, e.g. non-periodic sparse arrays [4][5][6], random arrays [7], spiral arrays [8] and Vernier arrays [5] each with their respective advantages and disadvantages [9] and b) those that address it through signal processing, where a sparse data set is captured and then the FMC data set is reconstructed [10]. An example is to use Deep Learning to artificially produce the remaining data of the Full Matrix [11].…”
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confidence: 99%
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“…Grating lobe suppression through optimised array design has been presented for LIPAs. Vernier and random 2D array layouts were designed for LIPAs, which were experimentally realised through a 2D scanning system [6].…”
Section: Introductionmentioning
confidence: 99%