The sensor array is a fundamental infrastructure for modern radar, sonar, and wireless communication systems. It has stimulated widespread implementations, ranging from national defense, remote sensing to the Internet of Vehicles (IoV). Direction-of-arrival (DOA) estimation and beamforming are two popular research topics in sensor arrays. Current research focuses on array signal processing with ideal assumptions (e.g., far-field sources, narrow-band signals, perfect waveforms, well-calibrated sensors, and white Gaussian noise).

Unfortunately, in practice, model errors always occur due to an imperfect scenario. Typical non-ideal scenarios include sensor mutual coupling, gain-phase error, broken sensor, coherent sources, and non-Gaussian noise. In the presence of model errors, the performances of DOA estimation and beamforming decrease significantly. Therefore, efforts should be made to help improve the robustness of the sensor array.

The aim of this Special Issue is to solicit original research and review articles discussing recent advances in signal processing with model errors. Authors are invited to submit submissions presenting new theoretical and/or application-oriented research including algorithms, models, technology, and applications.

Potential topics include but are not limited to the following:

• Array signal processing with mixed far-field and near-field sources
• Array signal processing with mixed coherent and non-coherent sources
• Array signal processing with mixed wide-band and narrow-band signals
• Array signal processing in the presence of mutual coupling
• Array signal processing in the presence of gain-phase error
• Array signal processing in the presence of sensor position error
• Array signal processing with partial sensor failure
• Array signal processing in the presence of combined sensor errors
• Array signal processing with non-Gaussian noise
• Array signal processing with non-perfect transmitting and receiving waveforms