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.
We comprehensively investigated the influence of laser wavelength on the detection distance at different clear air turbulence (CAT) intensities, distance resolutions, and Brunt–Väisälä frequency theoretically. It is found that there exists the optimal wavelength for maximal detection distance. When the distance resolution is fixed, the detection distance of 532 nm LiDAR is further compared with the 355 and 1064 nm counterparts and is more suitable under moderate to severe CAT. Our findings break the traditional cognition that “ultraviolet wavelength LiDAR is the most suitable for CAT detection” and may promote the remote detection research of CAT.
Sheared-beam imaging (SBI) is an effective way of imaging through turbulent medium, such as atmosphere or scattering liquid. Traditionally, the imaging is based on the laser transmitter array consisting of three beams or five beams for coherent illumination to the remote object. Compared with the existing SBI methods, the four-beam sparse sampling imaging method has been proposed, which may have more advantages; it not only sparses the detector elements but also reduces the number of emitted beams. However, the traditional phase retrieval algorithms are not suitable for the four-beam sparse sampling imaging. We propose a four-beam sparse phase retrieval (F-BSPR) algorithm, which uses the phase differences from both horizontal and vertical components and the phase differences from other components when the phase is retrieving. The proposed phase retrieval algorithm can better connect the phase difference and improve the accuracy of the phase retrieval. Furthermore, the imaging quality is improved. Simulation and experimental results show that the proposed algorithm is effective and feasible when the number of detector elements is sparse by 50%. Compared to the traditional four-beam phase retrieval method, the proposed F-BSPR method has better imaging quality and robustness.
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.
Coherent imaging with multi-beam laser is considered as a key technique in ground based imaging. In the paper, the composition of multi-beam laser coherent imaging system is demonstrated in detail, the constraints between subsystem parameters are analyzed, and the array layout of multi-beam laser imaging transmitter is proposed. In the system, the laser aiming accuracy has an important impact on the imaging. The theoretical simulation indicates that the aiming error of the emitter array should be controlled within 5%. Finally, Design equivalent aperture as Φ1.5m experimental system and Imaging target successfully, verifying the correctness and feasibility of the system, and promoting the implementation of multi-beams coherent imaging technology.
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