In ocean optics, salinity is an important inherent optical parameter to be measured. In the field of optics, refractive index (RI) is closely related to salinity. Through the real-time detection of the refractive index, we achieved the purpose of underway monitoring the salinity of seawater. We designed a refractive index measurement system based on optical total internal reflection. In this system, the detecting precision of the refractive index of the sea water reached 10<sup>-4</sup>. Through the conversion of the refractive index, we achieved in-situ measurement of the salinity. In 2016 summer, we accomplished a successful underway measurement in China Yellow Sea. The trends of the results from refractive index are basically agreed with the salinity measurements from electrical conductivity.
We present a method based on total internal reflection (TIR) phenomenon for measuring the refractive index (RI) distribution with high-precision. In the field of RI measurement, the method based on TIR phenomenon is usually used to detect the average RI of the sample under tested, but unable to get the detail of RI distribution. We present a new method, using the micro-lens array to split the beam of light and divide the testing surface into a certain number of tiny detection areas. With the detector of area CCD camera, each pixel collects the reflected light from each tiny detection area respectively. By analyzing the reflectivity to each tiny detection area, we can get RI information of each tiny area. Through theoretical calculation and the actual scaling, the RI value of each spot is obtained. After collecting the RI of each tiny area, we can obtain the RI distribution.
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.