Abstract

The inverse beamforming (IBF) is a mature method to improve azimuth resolution. However, for weak targets it is not applicable as IBF enhances side lobes. In this paper, an improved IBF algorithm is proposed to raise the azimuth resolution under the premise of ensuring the detection ability for weak targets. Firstly, from the point of phase compensation, we analyze the cause of side lobes when IBF is applied. Then the improved IBF algorithm recorded as GIBF (the improved inverse beamforming) is proposed by changing the Toeplitz average into the phase construction. The theoretical derivation and simulation data processing show the proposed method can improve the resolution of the N sensors to the standard of 2N − 1 sensors under different signal-to-noise ratios. Compared with IBF, GIBF has great advantages in detecting weak targets. Passive sonar data are used to further verify the advantages of GIBF; the trajectories on azimuth history diagrams become clear, the azimuth resolution is improved, and the detection ability for weak targets is still robust. In addition, GIBF is combined with the common DOA (direction of arrival) estimation algorithms, such as conventional beamforming and minimum variance distortionless signal response, which proves the applicability of the algorithm.

Highlights

  • In passive sonar azimuth estimation research, the most robust method is conventional beamforming (CBF)

  • Is applied on experimental data and the results showed that the detection capability for a weak target is robust and GIBF is beneficial for the improvement of the azimuth resolution

  • inverse beamforming (IBF) is the same as that of the (2N – 1)-element uniform linear array (ULA) CBF when only one target exists, which is consistent with the theoretical derivation above

Read more

Summary

Introduction

In passive sonar azimuth estimation research, the most robust method is conventional beamforming (CBF). Reference [8] applies IBF to synthetic aperture sonar This combination can effectively improve the detection performance of extended towed array technology. An improved IBF algorithm (recorded as GIBF) is proposed to eliminate the interference terms and preserve the array extension terms by changing the Toeplitz averaging process. This achieves the ability to increase the azimuth resolution and suppresses the interference introduced by the IBF algorithm.

Principle of IBF
Phase Compensation Analysis of IBF Theory
Cause of Side-Lobe Enhancement
GIBF Principle
Extension of GIBF Method
Weak Target Detection Capability of GIBF
Azimuth of GIBF
Comparison with
Comparison
Second
Experimental Data Verification
The comparison between methods: history diagram by azimuth
Conclusions
Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.