Potential Problems in Emerging Applications of Sparse Arrays 2021
1Nanjing University of Aeronautics and Astronautics, Nanjing, China
2McGill University, Montreal, Canada
3National University of Defense Technology, Hefei, China
Potential Problems in Emerging Applications of Sparse Arrays 2021
Description
Recently, sparse arrays, such as coprime array and nested array, have been considerably attractive to improve active and passive sensing in radar, navigation, under-water acoustics, and wireless communications.
Sparse array signal processing provides a systematic framework for sparse sampling and array structure with enlarged aperture, enhanced spatial resolution, increased degrees of freedom (DOFs), and reduced mutual coupling. Different co-array based approaches, e.g., spatial smoothing technique based algorithms, Toeplitz property based algorithms, and sparse reconstruction methods, can circumvent spatial aliasing and offer a unique response to targets with sparse sampling in time, space, and frequency. Temporal and spatial sparse samplings encounter merits in direction of arrival (DOA) estimation and adaptive beamforming.
This Special Issue is intended to encourage high-quality research in array signal processing techniques with sparse arrays and its applications in radar, sonar, wireless communications, and other fields. Authors are invited to submit papers presenting new research to tackle the potential problems in emerging applications of sparse arrays. All submissions must describe original research, not published or currently under review for another workshop, conference, or journal. The topics suggested can be discussed in terms of concepts, the state of the art, implementations, and running experiments or applications. The purpose of this Special Issue is to gather state-of-the-art research contributing to recent advances in the field of sparse array signal processing. Original research and review articles are welcome.
Potential topics include but are not limited to the following:
- Generalizations of co-prime and nested arrays for increased DOFs
- Array geometry optimization for high accuracy DOA estimation
- Sparse array calibration and mutual coupling effect
- Convex and nonconvex optimizations related to array signal processing
- Off-grid and grid-less solutions to super-resolution
- Sparse recovery-based methods for DOA estimation
- Robust DOA estimation in low SNR or small snapshot number
- Multi-dimensional sparse array signal processing
- Hardware implementation and design
- Applications to sonar, radar, MRI, geolocation, and other areas