In recent decades, imaging sonar has been the most widely employed remote sensing instruments in the field of underwater detection. The multibeam echo sounder (MBES) plays an important role in obtaining high-accuracy seabed topography. However, the resolution of the MBES substantially decreases with the increasing distance. Synthetic aperture sonar (SAS) achieves constant resolution on the along-track, improving the fineness of the image. However, conventional side-scan SAS usually only achieves 2D images, and gaps always exist. In this modeling and experimental research paper, we propose a novel underwater acoustic imaging scheme to improve the imaging performance of MBES, based on the complementarity of MBES and SAS systems. We design a 2D transducer array to increase the detection efficiency and obtain spatial gain. Moreover, the processing scheme is analyzed to design the working parameters in actual engineering applications. We exploit a target echo simulation approach to establish the research basics of the imaging algorithms, which also reflects the shapes and shadows of targets to match actual situations as realistically as possible. The proposed imaging algorithm synthesizes a virtual aperture receiving array on the along-track and reserves the multi-element manifold on the across-track. This helps to improve the imaging quality of the MBES and achieves high-resolution 3D detection with no gaps. Simulation and tank experimental results demonstrate that the proposed scheme can significantly improve the detection ability of the MBES, especially for small 3D target detection, thus making it suitable for 3D high-resolution underwater detection applications.

The inconsistency of magnitude and phase variations among the receiving array elements in multibeam soundings can seriously affect the beam pattern characteristics, which reduces the array gain, increases the side lobe level, and deteriorates direction of arrival (DOA) estimation. The accuracy of the beamforming result may be improved by correcting for magnitude and phase variations among the array elements. Therefore, a novel estimation and correction method based on near-field focused beamforming is proposed to overcome deficiencies of the conventional methods. The magnitude and phase variation model and the corresponding influence on the direction-finding accuracy are analyzed. The near-field focused beamforming model is established for multielement systems, and the root-mean-square error (RMSE) method is used to determine the ideal source incident angle for correction. We construct the receiving signal covariance matrix in the frequency domain and further estimate the magnitude and phase variations in each array element. The performance and effectiveness of the proposed method are verified by simulations and small anechoic tank experiments. The proposed method requires the employment of a rotation platform that providing necessary rotation information, and thus can accurately and effectively estimate and correct for variations in the magnitude and phase response of elements in the receiving array. The experimental results show that the sidelobe level can be reduced by approximately 3 dB after the array is corrected, and the angle deviation is reduced by approximately 0.1°.

The detection accuracy of the multibeam echo sounder (MBES) can be damaged severely and inevitably due to the mismachining tolerance of the transducer array. Therefore, it is necessary to demonstrate the performance of the multi-element transducer array to guarantee the accuracy of the processing algorithms. In this paper, a kind of multi-element MBES receiving transducer array self-calibrating method is proposed to manage the serious defocusing problem of the conventional methods. We analyze the error source and their effect on the MBES detection. The near-field beamforming and the least residual error criterion methods are employed to calibrate the average element spacing. The integrated self-calibrating method is managed to calibrate the transducer array, considering the coupling between the circuits and the element with a channel uniformity problem. An experiment is carried in a small-size tank to evaluate the method proposed. The outfield experimental data are compensated by the average element spacing and the beam response error estimated in the tank experiment. The simulations and the field data processing results indicate that the novel method proposed can effectively demonstrate the performance of the receiving transducer array and guarantee the coverage of the MBES system.

To solve the false terrain problem caused by the tunnel effect in the conventional multibeam seafloor terrain detection, a detection method of multibeam seafloor terrain based on the ADOS-CFAR (Amplitude Dichotomy Order-Statistics Constant False Alarm Rate) is developed. This paper first discusses the principles and existing problems of the OS-CFAR and K-FINDER algorithms and then suggests the ADOS-CFAR algorithm and its fast calculation method for those problems. By adopting this algorithm into the detection method of multibeam seafloor terrain and carrying out the simulation study on the computational load of the ADOS-CFAR, it is shown that this method has a lower computational load on the premise of ensuring the detection performance. Finally, the proposed algorithm is analyzed and verified through the test data in Songhua Lake. The result indicates that this method can effectively avoid the false terrain caused by tunnel effect with higher terrain detection accuracy.

Multibeam echo sounder (MBES) and synthetic aperture sonar (SAS) are effective image sonar systems used as the major underwater observation instruments. The MBES system can get the full-scan detection without gaps, while the resolution on the along-track is limited by the beam width and the range. The SAS system can provide the high resolution independent of signal frequency and range, while the accurate height information cannot be obtained directly and the gaps always exist. Multibeam SAS (MBSAS) is a new type of imaging sonar that combines the advantages of MBES and SAS. Through the MBSAS imaging algorithm, the full-scan 3-D detection without gaps can be obtained with high resolution. In a single synthetic period, the carrier should move linearly as an ideal track to guarantee the validity of the synthesis algorithm. However, the carrier’s motion error always exists in the actual situation. Thus, the carrier’s motion error should be estimated and compensated effectively to avoid the sonar image being defocused. In this paper, an echo model of MBSAS is proposed and an imaging algorithm is deduced to analyze the error of the imaging algorithm, which is caused by the motion error. The motion error is divided into six dimensions and separated into two types as the position error and the motion attitude error. The defocusing problem is caused by the joint motion error influences rather than the single dimension. A kind of joint motion error estimation algorithm is also proposed to estimate the motion error of the carrier. Through the simulation study, the feasibility and the performance of the algorithm are demonstrated. Simulation results indicate that the motion error can be estimated and the image defocusing problem can be handled effectively.