Direction of arrival (DOA) estimation, also known as direction finding, is an important topic in array signal processing. It has a wide range of applications in information warfare, radar, navigation, seismology, mobile communication, and other military and civil fields, and also has a broad application prospect, which has greatly attracted the attention of scholars all over the world.

With the development of artificial intelligence and intelligent optimization theory, classic DOA methods can benefit from these advanced technologies to cope with challenging scenarios. In order to meet the direction-finding requirements of mixed-signal sources, fast computing time, arbitrary array structure, high array utilization, and strong impulse noise background, mathematical derivation and analysis are considered indispensable. It is hoped that the received papers can break through the limitations of performance and applications for the existing DOA estimation algorithms, and promote the common development of direction finding and engineering mathematics domains.

This Special Issue welcomes original research and review articles focussing on the solutions of direction-finding engineering problems and the exploration of new direction-finding mathematical theory, further improving the performance of existing DOA estimation methods and expanding the application environment, and providing new ideas and methods for the theoretical research and engineering application of spatial spectrum estimation.

Potential topics include but are not limited to the following:

• DOA estimation and source number detection methods based on machine learning algorithms
• Data-driven techniques and deep learning for direction finding
• Derivation and design of new direction-finding equation aided by new intelligent optimization algorithms
• Robust DOA estimation method of arbitrary array structure under strong impulsive noise environment
• High precision direction finding method and array calibration based on sparse arrays
• Array geometry optimization for increased degrees of freedom and higher accuracy
• Grid-free direction-finding methods based on compressed sensing theory
• Direction finding with polarization-sensitive arrays
• DOA estimation in low SNR or small snapshots
• Dynamic distributed source direction-finding
• Direction finding method of single snapshot
• FDA-MIMO radar direction finding