Description

Multi-Channel Signal Processing has been the focus of tremendous theoretical advances and applications over the last nearly four decades, and continues to attract much attention by the signal processing community in both research and applications. Practical applications of multi-channel signal processing are found in many digital signal processing and communication systems for wireless communication, radar, sonar and biomedicine, just to mention a few. This special issue is to celebrate Professor Johann F. Böhme 80th birthday (26 January 2020). Johann was a pillar of multi-channel signal processing research worldwide who made fundamental contributions that paved the way and inspired many others to follow suit. His legacy as an academic advisor is most notable in generations of fine engineers and scientists that he produced. The special issue aims at attracting manuscripts on timely topics by signal processing practitioners. It will showcase recent research in digital signal processing for multi-channel signal processing with a focus on robustness. Robust statistical methods account for the fact that the postulated models for the data are fulfilled only approximately and not exactly. In contrast to classical multi-channel signal processing, robust methods are not affected much by small changes in the data, such as outliers or small model departures. They also provide near-optimal performance when the assumptions hold exactly. Prospective papers should be unpublished and present novel, fundamental research offering innovative contributions either from a methodological or an application point of view. Tutorial papers will also be considered.

Topics of interest include:

• Contributions are solicited in the following broad areas.
• 1. Robust adaptive beamforming methods
• 2. Robust parameter and direction-of-arrival estimation
• 3. Robust linear and non-linear model selection, signal detection and classification
• 4. Performance analysis of robust array processing methods
• 5. Antenna selection methods, sparse and minimum redundancy sensor arrays
• 6. Partly calibrated arrays, propagation in inhomogeneous media, non-stationary environments
• 7. Robust optimization methods in sensor array processing
• 8. Sensor array processing methods for real-life applications, such as wireless communications, multichannel radar/sonar systems, geophysics and machine and engine monitoring

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Guest Editors

• Prof. Abdelhak M. Zoubir (Technische Universität Darmstadt)
• Prof. Marius Pesavento (Technische Universität Darmstadt)
• Dr. Mohammed Nabil El Korso (Paris Nanterre University)
• Prof. Hing Cheung So (City University of Hong Kong)
• Prof. Xue Jiang (Shanghai Jiao Tong University)

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