2025_programme: Nested Array Beamforming Method Based on Covariance Matrix Reconstruction Processing

• Day: June 19, Thursday
    Location / Time: TBA at 15:30 - 16:30
• Last minutes changes: -
• Session: Poster session
  Organiser(s): N/A
  Chairperson(s): N/A
• Lecture: Nested Array Beamforming Method Based on Covariance Matrix Reconstruction Processing
  Paper ID: 2141
  Author(s): Chunnan SONG, Enming ZHENG, Yi LI, Hua FANG
  Presenter: Chunnan SONG
  Abstract: Aiming at the high background noise issue in the nested array beamforming algorithm for multi-target scenarios, this paper proposes a nested array beamforming method based on covariance matrix reconstruction. This method first applies the Khatri-Rao product function to perform a multidimensional transformation on the nested array covariance matrix, based on the correlation between the elements in its rows and columns, thereby increasing the array’s degrees of freedom. Then, the array data, after the increase in degrees of freedom, undergoes translation transformation and covariance matrix reconstruction. Next, the phase difference consistency of the diagonal elements of the covariance matrix is utilized to perform accumulation processing, further reducing the noise in the covariance matrix elements and improving the signal-to-noise ratio of the data used for nested array beamforming. Compared with conventional beamforming (CBF), numerical simulations and sea trials demonstrate that this method achieves a narrower beamwidth and can resolve multiple targets separated by 3° for a 32-element nested array. Additionally, compared with the existing nested array beamforming method (NA_CBF), this method reduces the background level of the output spatial spectrum by 12 dB, enabling the detection of weak targets.
• Corresponding author: Dr Chunnan SONG
  Affiliation: Institute of Acoustics, Chinese Academy of Sciences
  Country: China