Fast and accurate wideband sparse spatial spectrum estimation in an underwater strong interference environment

Area of Science:

• Signal Processing
• Underwater Acoustics
• Array Signal Processing

Background:

• Wideband sparse spatial spectrum estimation is crucial for high-resolution direction-of-arrival (DOA) estimation.
• Underwater environments with strong interference degrade DOA estimation accuracy and mask weak targets.

Purpose of the Study:

• To propose a fast matrix filter design method using truncated nuclear norm regularization.
• To attenuate strong interferences while preserving weak targets in DOA estimation.

Main Methods:

• A convex optimization problem is solved to obtain the matrix filter operator and filtered covariance matrix.
• A modified sparse spectrum fitting algorithm is applied with the designed matrix filter.
• Truncated nuclear norm regularization is employed for interference attenuation.

Main Results:

• The proposed method achieves higher DOA estimation accuracy compared to existing techniques.
• The method demonstrates a lower computational time for matrix filter design.
• Experimental results validate the enhanced estimation accuracy.

Conclusions:

• The fast matrix filter design effectively enhances DOA estimation accuracy in challenging underwater conditions.
• The method offers a computationally efficient solution for wideband sparse spatial spectrum estimation.
• This approach improves the detection of weak targets amidst strong interference.