Abstract
The problem of unimodular radar waveform design with similarity constraint in spectrally dense environment is considered. The corresponding optimization problem is nonconvex and additionally large-scale. Indeed, the waveform length can be of several thousands and the waveform has to be designed in every coherent processing interval. Since the problem is nonconvex, the majorization-minimization (MaMi) method is used for addressing it, and since it is large-scale, the alternating direction method of multipliers (ADMM) is adopted. Thus, we develop a computationally efficient approach for solving the problem by using MaMi with proper design of majorization function together with alternating ADMM with newly proposed computationally efficient proximal projections. We evaluate the computational cost of the proposed algorithm and show its fast convergence unmatched by existing approaches in terms of simulations.
Original language | English |
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Title of host publication | 2018 IEEE 10th Sensor Array and Multichannel Signal Processing Workshop, SAM 2018 |
Place of Publication | United States |
Publisher | IEEE |
Pages | 277-281 |
Number of pages | 5 |
Volume | 2018-July |
ISBN (Electronic) | 978-1-5386-4752-3 |
ISBN (Print) | 978-1-5386-4753-0 |
DOIs | |
Publication status | Published - 27 Aug 2018 |
MoE publication type | A4 Conference publication |
Event | IEEE Sensor Array and Multichannel Signal Processing Workshop - Sheffield, United Kingdom Duration: 8 Jul 2018 → 11 Jul 2018 Conference number: 10 |
Publication series
Name | Proceedings of the IEEE Sensor Array and Multichannel Signal Processing Workshop |
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ISSN (Print) | 1551-2282 |
ISSN (Electronic) | 2151-870X |
Workshop
Workshop | IEEE Sensor Array and Multichannel Signal Processing Workshop |
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Abbreviated title | SAM |
Country/Territory | United Kingdom |
City | Sheffield |
Period | 08/07/2018 → 11/07/2018 |