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