Underwater Lidar Research Articles

Color class and structure-related observable fluorescence response in arctic macroalgae as coastal underwater lidar substrates

In the context of underwater marine biological remote sensing surveys, we consider the fluorescence response of macroalgal and kelp targets to underwater fluorescence laser serial and lidar imaging applications. An investigation of absorption and fluorescence emission via excitation–emission (EEM) spectra of Arctic macroalgal substrates is presented via naturally and artificially generated structural scenarios. Fluorescence was found to increase with algal structure thickness for the kelp Alaria esculenta, both when its output is tested with or without structural modification (increase thickness) of the kelp thallus. Several trials involving other species of all three color classes showed fluorescence output decreased after a thickness increase via layering or structure reconfiguration: a process we suggest is due to fluorescence re-absorption sometimes occurring within and between the rearranged algal structures.

Reduction of lidar ranging error in turbulent water based on WT-ICA method

A new signal-processing method for the underwater lidar system based on wavelet transform (WT) and independent component analysis (ICA) is presented in this paper. Turbulence in water causes stronger scattering in underwater lidar returns, which can reduce the ranging accuracy and spatial resolution of the underwater lidar system. The method we proposed combines wavelet decomposition and independent component analysis (ICA), the data sets from wavelet decomposition are used to form the input matrix of ICA. The new method benefits from adaptive filtering of WT and blind source separation of ICA, therefore, the scattering clutters are further reduced. The WT-ICA signal processing algorithm is tested with experimental data. A mirror and a black Polyvinyl chloride (PVC) plate were used as the targets, respectively. Without using the WT-ICA, the ranging error with the mirror was 10.0 cm at 3 m distance when the attenuation coefficient of the water was 2.0 m-1. A pump was used to generate turbulence in the water tank. When the flow rate of the pump was 200 L/min, after using WT-ICA, the ranging error was reduced from 14.0 cm to 4.0 cm. For the PVC plate, the ranging errors were 4.5 cm and 19.0 cm at 6.0 attenuation length with and without the algorithm respectively. In both cases, applying this algorithm can significantly improve the ranging accuracy. When the algorithm is applied, the ranging error and detection probability of target echoes with and without turbulence were similar. These results indicated that the WT-ICA method had the ability to reduce the influence of turbulence.

Scattering Suppression in Underwater LIDAR Signal Processing Based on Wavelet-ICA Method

Scattering Suppression in Underwater LIDAR Signal Processing Based on Wavelet-ICA Method

Full-day profiling of a beam attenuation coefficient using a single-photon underwater lidar with a large dynamic measurement range.

A compact underwater lidar system, utilizing a single-photon detection technology, is proposed to effectively eliminate interference from the sea-air interface and enhance the accuracy of water optical property measurements. However, the high sensitivity of the single-photon detector poses challenges, including daytime operation difficulties due to strong solar radiation noise and detector saturation from near-field lidar signals. To address these issues, the laser and optical receiver of the lidar are optimized to suppress solar radiation noise, and a dual-telescope structure is introduced to improve the dynamic measurement range beyond 70 dB. In addition, a Monte Carlo simulation establishes the relationship between beam attenuation coefficients (c) and lidar attenuation coefficients (Klidar), enabling the retrieval of c profiles from Klidar. A field experiment conducted in the South China Sea, spanning from inshore to offshore waters, demonstrates the effectiveness of the lidar. The results highlight its potential applications, including the assessment of subsurface particulate organic carbon (POC).

Anti-scattering signal processing method of VMD-ICA based underwater lidar

This paper proposes an underwater signal processing method based on the combination of variational mode decomposition (VMD) and independent component analysis (ICA). In this method, the VMD is used to decompose a set of echo signals into groups of eigenmodal signals arranged according to the order of their frequencies. These modal signals are then used as an observation matrix for ICA to ensure the integrity of the separated target echo signals. In this method, the correlation between the decomposed modal signals and the original signal is used to select the signals which are used as input matrix rows for ICA. The signal-to-clutter ratio is used to determine the number of decomposed layers. The ICA is used to separate the scattering and target echoes, so as to recover the weak target echoes in the strongly scattered water and greatly improve the ranging accuracy. A 532 nm intensity-modulated continuous wave (CW) laser is used in the underwater ranging experiments. The attenuation coefficient of the water is changed by adding Mg(OH)<sub>2</sub>, ranging experiments are carried out at different attenuation lengths. The experimental results show that the signal processing method can be used to successfully measure the target within 9 AL (attenuation length) when the laser output power is 2.3 W, and the ranging accuracy is improved from 16 cm to less than 5 cm by using the algorithm. The proposed method can be applied to underwater lidar application in turbid water and long distance ranging underwater where the scattering dominates the echoes.

Application of Independent Component Analysis Method in Underwater Lidar

Application of Independent Component Analysis Method in Underwater Lidar

Enhanced Underwater LiDAR via Dual-Comb Interferometer and Pulse Coding

Enhanced Underwater LiDAR via Dual-Comb Interferometer and Pulse Coding

Day and night continuous high-resolution shallow-water depth detection with single-photon underwater lidar.

Single-photon lidar has emerged as a strong technology for bathymetric measurements. However, its heightened sensitivity additionally makes it susceptible to solar radiation noise, particularly in the green light wavelength where solar radiation is strong, posing challenges for its daytime operation. To address this issue, a single-photon underwater lidar system is proposed and demonstrated. This scheme has these features. 1) Underwater applications not only mitigate the impact of the air-water interface on laser transmission but also significantly attenuate solar radiation reaching the lidar due to the absorption and scattering properties of water. 2) The telescope is designed with a small aperture and narrow field of view to significantly suppress solar radiation. 3) A combination of a narrowband laser and narrowband filter technique is effectively employed to minimize residual solar radiation, thus enabling continuous bathymetric observation capabilities during both day and night. 4) After acquiring the backscattered signal from the bottom, a water depth extraction algorithm utilizing bi-Gaussian fitting is proposed. To demonstrate the robustness of the lidar and the effectiveness of the algorithm, the underwater single-photon lidar system is deployed on a ship to conduct cruise surveys of two bays in the nearshore area, as well as a full-day stationary observation experiment. The lidar measurements are highly consistent with the synchronized sonar observations. The full-day stationary observation experiment showcased its capability to deliver continuous measurements throughout the day and night. These results demonstrate the potential of the system in various applications, including high-precision underwater terrain mapping, obstacle avoidance for underwater platforms, and underwater target imaging.

Simulation and Design of an Underwater Lidar System Using Non-Coaxial Optics and Multiple Detection Channels

The efficacy of underwater laser detection is considerably impacted by the intense attenuation of light resulting from the scattering and absorption effects of water. In this study, we present the simulation and design of the underwater Lidar system that integrates the paraxial multi-channel detection strategy to enhance the dynamic range in subsea environments. To evaluate the performance of the system with multiple detection channels, we introduce a multi-channel underwater Lidar simulation (MULS) method based on the radiative transfer Lidar equations. Experimental validations were conducted under varied water conditions to assess the performance of the prototype and validate the simulation results. The measured range accuracy of each channel in the prototype is better than 0.1085 m, and the simulated and measured waveforms exhibit strong correlations, verifying the reliability and validity of the simulation method. The effects of transceiver configuration and the maximum detectable range of different detection methods were also discussed. Preliminary results indicate that the paraxial multi-channel design effectively suppresses near-field backscattering and substantially enhances the maximum detectable range. The findings presented in this study may provide valuable insights for the design and optimization of future underwater laser detection systems.

Submerged single-photon LiDAR imaging sensor used for real-time 3D scene reconstruction in scattering underwater environments.

We demonstrate a fully submerged underwater LiDAR transceiver system based on single-photon detection technologies. The LiDAR imaging system used a silicon single-photon avalanche diode (SPAD) detector array fabricated in complementary metal-oxide semiconductor (CMOS) technology to measure photon time-of-flight using picosecond resolution time-correlated single-photon counting. The SPAD detector array was directly interfaced to a Graphics Processing Unit (GPU) for real-time image reconstruction capability. Experiments were performed with the transceiver system and target objects immersed in a water tank at a depth of 1.8 meters, with the targets placed at a stand-off distance of approximately 3 meters. The transceiver used a picosecond pulsed laser source with a central wavelength of 532 nm, operating at a repetition rate of 20 MHz and average optical power of up to 52 mW, dependent on scattering conditions. Three-dimensional imaging was demonstrated by implementing a joint surface detection and distance estimation algorithm for real-time processing and visualization, which achieved images of stationary targets with up to 7.5 attenuation lengths between the transceiver and the target. The average processing time per frame was approximately 33 ms, allowing real-time three-dimensional video demonstrations of moving targets at ten frames per second at up to 5.5 attenuation lengths between transceiver and target.

Fractal superconducting nanowire single-photon detectors working in dual bands and their applications in free-space and underwater hybrid LIDAR.

We demonstrate a fiber-coupled fractal superconducting nanowire single-photon detector (SNSPD) system with minimum polarization dependence of detection efficiency. Its system detection efficiency (SDE) was maximized at the wavelength of 1540 nm, which was measured to be 91 ± 4%; furthermore, we observed the second local maximum of SDE at the wavelength of 520 nm, which was measured to be 61 ± 2%. This dual-band feature of SDE was due to the enhancement of the optical absorptance by two longitudinal resonance modes of the micro-cavity. By using high SDE with minimum polarization dependence in these two bands, we implemented a hybrid LIDAR for imaging the remote objects in free space and under water.

Application of CEEMDAN combined wavelet threshold denoising algorithm to suppressing scattering cluster in underwater lidar

<sec>The echo of underwater lidar often contains a significant quantity of scattering clutters. In order to effectively suppress this scattering clutter and improve the ranging accuracy of underwater lidar, a novel denoising method based on complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) and wavelet threshold denoising is proposed.</sec><sec>The CEEMDAN-wavelet threshold denoising algorithm uses the correlation coefficient to select intrinsic mode function (IMF) components obtained from the CEEMDAN decomposition. The IMFs, which are more closely related to the original signal, are selected. Then, the wavelet thresholding denoising algorithm is applied to each of the selected IMFs to perform additional denoising. For each IMF component, specific threshold values are calculated based on their frequency and amplitude characteristics. Subsequently, the wavelet coefficients of the IMF components are processed by using these threshold values. Finally, the denoised IMF components are combined and reconstructed to obtain the final denoised signal. Applying the wavelet threshold denoising algorithm to IMF components can effectively remove noise components that cannot be removed by traditional CEEMDAN partial reconstruction methods. By using the threshold value calculated based on the characteristics of each IMF component, the wavelet thresholding denoising process is improved in comparison with directly using a single threshold value. This approach enhances the algorithm’s adaptability and enables more effective removal of noise from the signal.</sec><sec>We apply the proposed method to underwater ranging experiments. A 532 nm intensity-modulated continuous wave laser is used as a light source. Ranging is performed for a target in water with varying attenuation coefficients. A white polyvinyl chloride (PVC) reflector is used as a target. When the correlation extreme value is directly used to determine the delay at a distance of 3.75 attenuation length, it results in a ranging error of 19.2 cm. However, after applying the proposed method, the ranging error is reduced to 6.2 cm, thus effectively improving the ranging accuracy. These results demonstrate that the method has a significant denoising effect in underwater lidar system.</sec>

Compact Long-Range Single-Photon Underwater Lidar With High Spatial–Temporal Resolution

Oceanic lidar has emerged as a strong technology for oceanic three-dimensional remote sensing. However, most existing oceanic lidars are bulky and high-power consumption, thus difficult to enable underwater operation. Here we present a compact single-photon lidar system for long-range underwater measurement. A single-photon detector was adopted to achieve a high signal-to-noise ratio. Benefiting from the single-photon sensitivity in detection, long-range active detection was realized with a low pulse energy laser at 1 μJ and a small-aperture coupler at 12 mm. Moreover, a narrow linewidth picosecond fiber laser with high repetition rate was employed to guarantee a high spatial resolution and high update rate. A fiber-connected configuration was specially designed for the miniaturized and robust structure in an optical receiver. In an experimental demonstration, the profile of backscattered signal from clean water was obtained over 70 m with high spatial-temporal resolution to demonstrate the capability of this lidar system. The maximum detection distance of the single-photon lidar reaches ~3.6/ <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">K_d</i> ( <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">K_d</i> , diffuse attenuation coefficient) for waterbody and up to 5.5/ <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">K_d</i> for a hard target. Furthermore, it exhibits a high update rate capability and realizes the localization and quantification of underwater bubbles up to 26 m away at a high update rate of 100 Hz. These results indicate its potential in a variety of applications including remote sensing of marine biogeochemical parameters, the quantification of seabed gas emissions, and long-range underwater imaging.

Ranging accuracy improvement by using a spiral phase plate in a time-of-flight underwater lidar system

We report on an investigation of spatial coherence filtering using a spiral phase plate (SPP) to reduce the amount of scattered light collected in an underwater lidar. This approach exploits the difference in spatial coherence between target-reflected light and scattered light as a means of separating and filtering out the multiple-scattered clutters. An underwater target was illuminated by a Gaussian beam, and both the target-reflected light and scattered light passed through an SPP. The spatially coherent target-reflected component formed a ring-shaped vortex beam, while the spatially incoherent scattered component was unaffected and remained a centrally stronger distribution obeying the Mie scattering law. A mask was placed behind the SPP which allowed only the light on the vortex ring to pass through. Therefore, an all-optical spatial coherence filter composed of an SPP and a mask provides an effective way to reject undesired scattered light without affecting the target-reflected light. A numerical simulation based on Zemax software was carried out and showed that the approach reduces the power of received scattered light without changing the power of received target-reflected light. Experimental results showed that the approach reduced the temporal broadening and excessive delay of the returned pulse caused by forward scattering, therefore reducing the ranging error. Moreover, using a vortex beam with a bigger topological charge improved the ranging accuracy more obviously, especially in turbid water. When the attenuation length was 12.5, by using a 40th-order SPP, the ranging error was reduced from 18 cm to 5.3 cm with a diffuse target.

Reduction of Scattering Clutters in an Underwater Lidar System by Using an Optical Vortex

An optical vortex was applied in an underwater lidar system to improve ranging accuracy. A self-developed intensity modulated continuous wave 532 nm laser beam was used as the light source. The detector was a photomultiplier tube (PMT). The output signal from the PMT was correlated with a reference signal to retrieve the distance of the target. A spiral phase plate (SPP) was inserted before the detector to convert the spatially coherent target reflection onto an optical vortex ring. A mask with a transparent ring that matched the vortex was used to block the scattering light distributed inside and outside the ring. Experimental results showed that the ranging error was significantly reduced in a turbid medium by the method, in addition, a high-order SPP worked better. With a 24-order SPP, we obtained a ranging error reduction from 20 cm to 2.73 cm when the attenuation length was 9.

Adjacent Frame Difference with Dynamic Threshold Method in Underwater Flash Imaging LiDAR

During the underwater LiDAR imaging process, the images achieved by the conventional constant threshold adjacent frame difference (AFD) method normally loses the distance information of targets. This is mainly due to the Gaussian distribution of the laser light intensity field, which leads to the inhomogeneous intensity distribution in the frame from the target acquired by intensity charge-coupled devices (ICCD). In order to overcome this issue, the novel dynamic threshold adjacent frame difference (DTAFD) method was proposed in this paper. The DTAFD method modifies the intensity threshold following the pixel intensities in the different parts of the single frame intensity image acquired by ICCD. After the detailed theoretical demonstration of the DTAFD method, with the purpose of verifying its feasibility, the self-developed range-gated flash imaging LiDAR has been employed to construct the distance images of the rectangular and circular shaped targets at different distances. The distance between the rectangular target and the LiDAR system is 25.7 m, and the circular target is 70 cm further away from the rectangular target. The full distance information of these two targets is obtained by the DTAFD method with an effectively suppressing noise and the PSNR is increased from 6.95±0.0426 dB to 7.62±0.0264 dB. The experimental results indicate that the DTAFD method efficiently solves the AFD method’s drawback on the target information loss caused by the unequal optical field distribution, which makes it more suitable for the scenarios with uneven laser distribution such as the underwater imaging environment.

Backward scattering suppression in an underwater LiDAR signal processing based on CEEMDAN-fast ICA algorithm.

A new signal-processing method to realize blind source separation (BSS) in an underwater lidar-radar system based on complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) and independent component analysis (ICA) is presented in this paper. The new statistical signal processing approach can recover weak target reflections from strong backward scattering clutters in turbid water, thus greatly improve the ranging accuracy. The proposed method can overcome the common problem of ICA, i.e. the number of observations must be equal to or larger than the number of sources to be separated, therefore multiple independent observations are required, which normally is realized by repeating the measurements in identical circumstances. In the new approach, the observation matrix for ICA is constructed by CEEMDAN from a single measurement. BSS can be performed on a single measurement of the mixed source signals. The CEEMDAN-ICA method avoid the uncertainty induced by the change of measurement circumstances and reduce the errors in ICA algorithm. In addition, the new approach can also improve the detection efficiency because the number of measurement is reduced. The new approach was tested in an underwater lidar-radar system. A mirror and a white Polyvinyl chloride (PVC) plate were used as target, respectively. Without using the CEEMDAN- Fast ICA, the ranging error with the mirror was 12.5 cm at 2 m distance when the attenuation coefficient of the water was 7.1 m-1. After applying the algorithm, under the same experimental conditions, the ranging accuracy was improved to 4.33 cm. For the PVC plate, the ranging errors were 5.01 cm and 21.54 cm at 3.75 attenuation length with and without the algorithm respectively. In both cases, applying this algorithm can significantly improve the ranging accuracy.

Near ultraviolet photonic integrated lasers based on silicon nitride

Low phase noise lasers based on the combination of III–V semiconductors and silicon photonics are well established in the near-infrared spectral regime. Recent advances in the development of low-loss silicon nitride-based photonic integrated resonators have allowed them to outperform bulk external diode and fiber lasers in both phase noise and frequency agility in the 1550 nm-telecommunication window. Here, we demonstrate for the first time a hybrid integrated laser composed of a gallium nitride-based laser diode and a silicon nitride photonic chip-based microresonator operating at record low wavelengths as low as 410 nm in the near-ultraviolet wavelength region suitable for addressing atomic transitions of atoms and ions used in atomic clocks, quantum computing, or for underwater LiDAR. By self-injection locking of the Fabry–Pérot diode laser to a high-Q (0.4 × 106) photonic integrated microresonator, we reduce the optical phase noise at 461 nm by a factor greater than 100×, limited by the device quality factor and back-reflection.

Underwater LiDAR Image Enhancement Using a GAN Based Machine Learning Technique

Robust underwater imaging sensors are essential in applications such as identifying and classifying marine animals in turbid waters, typically found around coastal monitoring sites. The Unobtrusive Multi-static Serial LiDAR Imager (UMSLI) has been developed to capture images taken in degraded underwater environments and provides superior range and image contrast over conventional optical cameras. In contrast to traditional underwater LiDAR systems that employ blue-green lasers, UMLSI will not harm the vision of marine animals, which is an important aspect in such settings. As with any other underwater LiDAR sensors, improving the quality of images taken in highly turbid water is essential to the UMSLI system. This paper proposes a novel machine learning image enhancement technique based on a Generative Adversarial Network (GAN) framework. One main contribution of the method is the incorporation of a correntropy-based perceptual loss. This technique has shown to be effective in enhancing ground-based images and has been adapted for LiDAR image enhancement. Given the limitation of existing underwater LiDAR data, a method for simulating degraded data for training is also presented. This LiDAR technique was validated using LiDAR data captured by the UMSLI system within Florida Atlantic University&#x2019;s Harbor Branch Oceanographic Institute (FAU-HBOI) optical test facility and at the Marine and Coastal Research Laboratory at the Pacific Northwest National Laboratory (MCRL-PNNL). This image enhancement technique can be readily extended to other underwater LiDAR systems.

Numerical Simulation of Performance Improvement of Underwater Lidar by Using a Spiral Phase Plate as Spatial Filter

In turbid water, target reflected lidar signal is easily buried in &#x201C;clutter&#x201D; due to scattering. We proposed an underwater laser ranging model applying an optical vortex in the receiver to separate the scattering clutter from the target reflected signal. A spiral phase plate (SPP) was placed in front of the detector to convert the target reflected Gaussian beam to an optical vortex. While the scattering clutters were not able to be converted due to the loss of spatial coherence. Therefore, the target reflected signal and scattering clutters were spatially separated by the SPP. An underwater laser detection simulation using Zemax software was carried out. The numerical simulation showed that when the SPP was placed in front of the receiver, the contrast of signal to clutter of the detection was improved by blocking the scattering clutters which had a Gaussian distribution at the center on the detection plane. The effects of beam divergence and orbital angular momentum (OAM) order to the lidar performance were also analyzed.