High-Quality MIMO Sonar Imaging Using Cross Correlation Suppression

Multiple-input–multiple-output (MIMO) sonar systems enhance imaging resolution by synthesizing a virtual array produced by orthogonal transmitted waveforms and a bank of matched filters. Up- and down-chirp pulses are widely used due to their approximate orthogonality and robustness for underwater remote sensing applications. However, the cross correlation function (CCF) terms between them always exist and thereby degrade the quality of the MIMO sonar image. In this letter, we propose a novel cross correlation suppression method for improving the image quality of MIMO sonar. The proposed method leverages the frequency-domain differences between the envelopes of autocorrelation functions (ACFs) and CCFs of up- and down-chirp pulses. After the Fourier transformed, the envelopes of ACFs are approximately to be square wave function, while CCFs are approximately to be sinc function. Therefore, CCFs’ energy is concentrated and easier to be suppressed. By setting the main components of the CCFs to zero in the frequency domain of the multibeam outputs’ envelopes, the method effectively suppresses range sidelobes (SLs) caused by cross correlation, thereby enhancing the quality of the imaging results. Through numerical simulations and lake experiments, we quantitatively analyze the performance of the proposed method and demonstrate its effectiveness in MIMO sonar imaging.