Underwater platforms provide long-term detection of undersea targets. In this paper, we propose a method for the estimation of target motion parameters by submerged static acoustic detection equipment. The proposed method is based on the Radon transform of modeling the target moving in a uniform straight line. The heading angle, the time to the closest point of approach (CPA), and the ratio of velocity to the horizontal range of the target at the CPA to the sensor are obtained by applying the generalized Radon transform (GRT) to bearing–time records. The velocity of the target is determined by applying the GRT to the line-spectrum–time records. Furthermore, the motion trajectory of the target with respect to the detection equipment can be calculated from the above parameters. To validate the feasibility and performance of the proposed method, computer simulations and sea trials based on a fixed single vector measurement system were analyzed in this paper. The results suggest that the proposed method can accurately estimate the motion parameters and can calculate the trajectory of the moving vessel along a straight line at constant velocity.

Underwater acoustic imaging (UAI) can be utilized to observe the spatial distribution of a near-field sound source. The image quality depends on the resolution and sidelobe level of conventional beamforming. The linear array based UAI can be considered as deconvolution of a two-dimensional point spread function shift-variant model. The performance of UAI can be improved via innovative deconvolution algorithms. In this study, a non-uniform spatial resampling Richardson-Lucy (RL) fast algorithm is designed in which the amount of samples is determined by the power of the UAI output. This allows for a significant decrease in the number of samples compared to the traditional RL algorithm with similar positioning accuracy. Computer simulations and sea trials are performed to validate the effectiveness and feasibility of the proposed method.

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