Single-photon LiDAR offers single-photon sensitivity and picoseconds timing resolution, leading to high-resolution three-dimensional (3D) images. In this paper, we investigate the reconstruction of 3D images from data acquired using a custom designed time-of-flight scanning transceiver based on the time-correlated single-photon counting LiDAR. The system comprises a pulsed laser source at 1064nm wavelength, a monostatic scanning transceiver and a superconducting nanowire single-photon detector. The maximum distance of ranging finding under the experimental environments is up to 95.1km, and high-resolution 3D image of a pavilion is reconstructed at the range of 2.9km. A total variation restoration optimization algorithm is performed to reduce the acquisition time of the entire 3D images. Experimental results show that this system is feasible for imaging at longer range by refining the setup, and have potential for target recognition.
In this paper, we designed a compact Mie scattering lidar system for ocean-atmospheric horizontal visibility measuring and an algorithm used for obtaining the visibility of the aerosol. The effective range of our lidar system was from 300 m to 3 km with a 7.5-m horizontal range resolution and a 1-min time resolution. To reduce the uncertainty caused by using slope method which based on the hypothesis that either molecule or aerosol components exist in the atmosphere, we used the two-component fitting method to retrieve the aerosol extinction coefficient and the calculated the visibility based on Koschmieder’s theory. The whole system was powered by electricity supply which made it easy mounting on a ship or observation station by the sea. Lots of experiments were conducted laboratory to ensure the veracity and stability. In 2016 summer, we joined the cruise survey in China Bo-Hai and Huang-Hai Sea. Site experiments were carried out on the research vessel ‘Dongfanghong 2’. The results showed that the visibility values obtained by our system were in good agreement with the value set by the visibility meter and our lidar system was able to achieve visibility measuring under different weather conditions.
Based on optical total reflection critical Angle method, we have designed a refractive index measurement system. It adopted a divergent light source and a CCD camera as the occurrence and receiver of the signal. The divergent light source sent out a bunch of tapered beam, exposure to the interface of optical medium and sulfuric acid solution. Light intensity reflected from the interface could be detected by the CCD camera and then sent to the embedded system. In the DSP embedded system, we could obtain the critical edge position through the light intensity distribution curve and converted it to critical angle. Through experiment, we concluded the relation between liquid refractive index and the critical angle edge position. In this system, the detecting precision of the refractive index of sulfuric acid solution reached 10<sup>-4</sup>. Finally, through the conversion of the refractive index and density, we achieved high accuracy online measurement of electrolyte density in lead-acid battery.
In this paper, we designed a pint-sized underwater pulsed lidar system for underwater obstacles detection based on a 532nm Nd-YAG pulsed laser as a source and a Hamamatsu photomultiplier tube (PMT) as a detector. In order to acquire the location of the obstacles, an algorithm was devised to handle the echo signal. Through this algorithm, the background noise was suppressed and the accurate range information of the target was obtained. A high-capacity lithium battery was employed to support this lidar system operating as long as eight hours continuously. To ensure our lidar system working steady in the natural underwater environment, a stable waterproof housing was designed for the system which has good water-tightness at 40m depth underwater. This system is small, compact and hand-held. An experiment was conducted in laboratory which proof that the system can achieve target detection within 25m. At last, this lidar system was tested in natural underwater environment of Fuxian Lake in Yunnan Province. There are lots of organic particles and other impurity particles in Fuxian Lake and the attenuation coefficient of the lake is about 0.67m<sup>-1</sup>. The results showed that this small-size lidar system was able to catch sight of the target within 20 meters and perform smoothly in the natural underwater environment.
Multiangle dynamic light scattering (MDLS) compensates for the low information in a single-angle dynamic light scattering (DLS) measurement by combining the light intensity autocorrelation functions from a number of measurement angles. Reliable estimation of PSD from MDLS measurements requires accurate determination of the weighting coefficients and an appropriate inversion method. We propose the Recursion Nonnegative Phillips-Twomey (RNNPT) algorithm, which is insensitive to the noise of correlation function data, for PSD reconstruction from MDLS measurements. The procedure includes two main steps: 1) the calculation of the weighting coefficients by the recursion method, and 2) the PSD estimation through the RNNPT algorithm. And we obtained suitable regularization parameters for the algorithm by using MR-L-curve since the overall computational cost of this method is sensibly less than that of the L-curve for large problems. Furthermore, convergence behavior of the MR-L-curve method is in general superior to that of the L-curve method and the error of MR-L-curve method is monotone decreasing. First, the method was evaluated on simulated unimodal lognormal PSDs and multimodal lognormal PSDs. For comparison, reconstruction results got by a classical regularization method were included. Then, to further study the stability and sensitivity of the proposed method, all examples were analyzed using correlation function data with different levels of noise. The simulated results proved that RNNPT method yields more accurate results in the determination of PSDs from MDLS than those obtained with the classical regulation method for both unimodal and multimodal PSDs.