Mathematical Problems in Engineering

Array Signal Processing with Imperfect Scenarios


Publishing date
01 Dec 2020
Status
Closed
Submission deadline
24 Jul 2020

Lead Editor

1Yangtze University, Jingzhou, China

2Hainan University, Haikou, China

3Nanjing University of Aeronautics and Astronautics, Nanjing, China

4Dalian University of Technology, Dalian, China

This issue is now closed for submissions.
More articles will be published in the near future.

Array Signal Processing with Imperfect Scenarios

This issue is now closed for submissions.
More articles will be published in the near future.

Description

Array signal processing is an essential area with numerous applications in radar, sonar, and wireless communications. Many efforts have been devoted and various methods have been proposed. Up to now, most of the existing works are based on ideal scenarios, for example, well-calibrated sensors, idea waveforms, and white Gaussian noise.

In engineering applications, however, imperfect scenarios may exist, and a model mismatch would appear between the ideal one and the real one. As a result, existing algorithms may fail to work. There is a strong requirement for robust array signal processing frameworks for such scenarios.

The aim of the Special Issue is to collate original research articles with a focus on array signal processing with imperfect scenarios. Review papers discussing the current state of the art are also welcome.

Potential topics include but are not limited to the following:

  • Adaptive beamforming
  • Direction-of-Arrival estimation
  • Radar imaging
  • Gain-phase error
  • Mutual coupling
  • Position error
  • Non-Gaussian noise
  • Off-grid problems
  • Combined sensor errors
  • Deep learning for error calibration
Mathematical Problems in Engineering
 Journal metrics
Acceptance rate27%
Submission to final decision64 days
Acceptance to publication34 days
CiteScore1.800
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Impact Factor1.305
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Article of the Year Award: Outstanding research contributions of 2020, as selected by our Chief Editors. Read the winning articles.