Multiplepath Matching Pursuit Using a Random Virtual Array Set Construction and Validation Technology for Target Bearing Detection with an Underwater Vector Coprime Array

The coprime array, proposed in recent years as a special type of sparse array, combines the advantages of sparse sensing with the unique properties of prime numbers, enabling a larger array aperture and higher degrees of freedom with the same number of physical sensors. In underwater array signal processing, the high-resolution potential of coprime arrays has attracted significant attention. However, in complex ocean environments, leveraging the advantages of coprime arrays to achieve high-resolution and robust target detection still faces challenges posed by sensor failures. Element failures can disrupt the physical structure of the coprime array, leading to significantly increased energy in grating lobes and side lobes of the beam pattern, thereby raising the probability of false target azimuth identification. To address this issue, this paper analyzes the virtual array set mapped from the physical coprime array and proposes a multiplepath matching pursuit method for underwater vector coprime array target azimuth detection based on random virtual array set construction and verification techniques. Cases of continuous and non-continuous virtual arrays are analyzed, and corresponding solutions are proposed. Through simulations and analyses of sea trial data, it is demonstrated that the proposed method can achieve high-resolution target azimuth detection as well as robust target detection in the presence of physical sensor failures.