Compared to traditional underwater cameras, lidar can capture more dimensional information about targets, thereby offering substantial advantages in underwater target detection. The Single-Slit Streak Tube Imaging Lidar (SS-STIL) is a high temporal resolution device designed for 3D precision measurement. It operates on the principle of time-of-flight, recording the 3D information of target as multiple high-precision 2D streak images. These images are then used to reconstruct the target's 3D information through advanced reconstruction algorithms. Existing researches on the imaging quality of Streak Tube Imaging Lidar (STIL) often fall short in thoroughly investigating the impact of water turbidity on imaging quality and particularly lack quantitative measurements of underwater imaging environments. To address the aforementioned issues, we first performed theoretical calculations and simulations of the SS-STIL for imaging targets in both air and underwater environments. Based on these simulation results, we determined the parameters for the main modules of the actual imaging system. We measured the water's attenuation coefficient in the experimental setting using a photometer, quantified five levels of underwater turbidity, and conducted experiments with our SS-STIL under these five different conditions. At an imaging distance of 4.5m and a water attenuation coefficient of 0.51m-1 , our SS-STIL system achieved an imaging resolution of 1cm and a spatial resolution of 3cm, which is superior to other existing STIL systems.
In the imaging of low-orbit moving objects, the number of detector elements in the traditional sheared-beam imaging (SBI) system is too great, which seriously restrict the application of SBI. In this paper, the detector array is sparse in two dimensions. We propose a two-dimensional sparse sampling imaging method, which emits a two-dimensional coherent laser array, carries more spectral information of the target at a time and receives speckle echo signals by a two-dimensional sparse detector array for computational imaging. This method can reduce the number of detector elements many times. Firstly, the principle of two-dimensional sparse sampling with SBI detector array is deduced theoretically. Secondly, a two-dimensional spatial sparse reconstruction algorithm is investigated. The target amplitude product and phase difference carried by each detector array element is estimated using discrete Fourier transform, then the target amplitude product and phase difference of all detector array elements are matched respectively to form a complete target amplitude product surface and phase difference surface. The formulas of phase recovery and amplitude demodulation are derived. Finally, the validity and feasibility of the proposed method are verified by simulation. Compared with the traditional three-beam method, when the number of lasers in emission array is M×N, the number of detector elements is reduced to 1/(M-1)/(N-1) of the original without loss of imaging resolution.
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