The real-time data acquisition system (RTDAQS) in the bathymetric light detection and ranging (LiDAR) instrument, named “GQ-Cormorant 19”, previously developed by our group cannot completely acquire the echo data from the water surface and water bottom owing to the inaccurate determination of the instant of echo signal acquisition, resulting in echo data loss. Therefore, this study developed an adaptive echo signal acquisition method based on a field-programmable gate array (FPGA) chip. The proposed method utilizes the flying height for roughness adjustment, and the peak of echo signal detection and the fine adjustment are combined to accurately determine the instant of echo signal acquisition. The improved RTDAQS onboard the GQ-Cormorant 19 was mounted on unmanned aerial vehicle (UAV) and unmanned surface vessel (USV) platforms and the performance was verified through an indoor corridor and several outdoor water fields. The experimental results demonstrated that the improved RTDAQS can improve the effective echo data rate by 11.5% when compared with the previously developed RTDAQS. Therefore, it can be concluded that the improved RTDAQS can implement the adaptive high-speed acquisition of echo data and obtain high-quality echo data acquisition on various platforms, such as UAV and USV.

Existing photomultiplier tube (PMT)-based gating control systems embedded in bathymetric light detection and ranging (LiDAR) devices cannot automatically adjust the PMT gain in real time, resulting in the saturation distortion of echo signals or failure to receive echo signals. Therefore, this study proposes an adaptive adjustment method for the laser energy and PMT gain based on the self-feedback of echo data from a high-speed sampling and storage system. Zynq-7000 All Programmable SoC (ZYNQ) was used as the master controller, and the echo data analysis module, laser energy adjustment module, and PMT gain adjustment were designed based on the field-programmable gate array (FPGA). The corresponding control software was developed based on the ARM end to call the custom IP cores. The proposed method was experimentally validated using indoor corridors and outdoor water areas, such as pools, reservoirs, Wujiu Beach, and the Beibu Gulf. The experimental results demonstrated that the proposed method could adaptively adjust laser energy and PMT gain, with which the voltage amplitude fluctuation range of the echo signal was effectively reduced from the original -1.7 V–0 V (acquisition range of high-speed sampling and storage system) to -1.04 V– -0.26 V. With the comparative verification with multibeam sounder, the mean and standard deviation of the difference between the Z coordinates are -0.21 and 0.15, respectively, which indicates that the LiDAR using the proposed method achieves a similar accuracy of bathymetry.

The modeling of the LiDAR underwater echo signal is mainly divided into analytical and statistical methods. In this paper, the radiation transfer equation of LiDAR underwater transfer is established according to the QSSA approximate analytical method theory. For Katsev, the Green function is directly used to solve the radiation transfer equation, and the spectral element method is proposed to calculate the LiDAR radiation flux in the radiation transfer equation. To verify the accuracy of the LS-SEM-Katsev analytical model, the simulation results of the LS-SEM-Katsev analytical model and Semi-MC statistical model are verified under three typical seawater optical parameters. The experimental results show that the decision coefficients of the three simulation models are all above 0.99, which is highly consistent. A comparison between the computational times of LS-SEM-Katsev and Semi-MC simulation models showed that the computational efficiency of the proposed analytical model was 8 orders of magnitude higher than that of the Semi-MC model.

A traditional bathymetric LiDAR (light detection and ranging) has disadvantages such as large volume, heavy weight, necessity for airport and runway, and high cost for operation. For these reasons, this paper presents an off-axis four-reflection optical structure for single-band (532 nm) bathymetric LiDAR carried on UAV (Unmanned Aerial Vehicle). This optical system fully considers characteristics of the laser echo energy under different water conditions, which relate with the optical system parameters, such as peak power of laser emission, field of view (FOV), receiver aperture area, etc. The proposed optical system designs the objective lens, which are composed of one APD detector and two PMT detectors, the primary mirror, the second mirror, the plane mirror and the third mirror, two split field mirrors that separate the echo signals from shallow water, medium water and deep water, respectively. This proposed optical system was verified in laboratory tank, swimming pool, Lijiang River, lake, and the Qiaogang Sea Bay. It is found that the maximum water depth measured can reach 25.0 m with an error less than 0.1 m averagely. The dimension and weight of this LiDAR reach 90mm×160mm×90mm, and 10.25 kg, respectively, which is lightest and smallest bathymetric LiDAR worldwide.

Bathymetric light detection and ranging (LiDAR), which uses a laser with narrow pulse width and a high-repetition-rate, requires a real-time data acquisition system (RTDAQS) for quickly transmitting data with the characteristic of high sampling rates, high resolution and high accuracy. However, none of the RTDAQS in the world has reached these requirements. For this reason, this paper presents a RTDAQS with high speed SerDes data transfer technology based on the architecture of ADC+FPGA+ZYNQ. This RTDAQS consists of acquisition board and storage board. The acquisition board integrates high-speed analog-to-digital converter (ADC) acquisition module, Input/Output (I/O) control module, data transmission module, and Field Programmable Gate Array (FPGA) chip module. The storage board integrates FPGA Mezzanine Card (FMC) interface, solid state and ZYNQ chips. The corresponding software includes configuration for high-speed ADC acquisition module, I/O control module, data transmission module, and FMC interface module. The RTDAQS, which is embedded in the LiDAR with laser pulses width of 2.5ns ± 0.2ns and frequency of 500 Hz, has been verified by the experiments in indoor sink, outdoor pond, river, reservoir, Beihai Bay of the Pacific Ocean. The experimental results and comparison experiments demonstrate that the presented RTDAQS can reach a sampling rate of 2 GSPS and a sampling resolution of 14 bits and a sampling accuracy of 6 LSB with an acquisition error within 0.1 m, which meet the demands of high sampling rate with high accuracy data acquisition and quick data transmission in practice and can be applied to various devices.

High-quality waveform decomposition, as one of the most critical cores of light detection and ranging (LiDAR) data processing, has become increasingly interesting. However, the current Gaussian decomposition method cannot handle the superimposed waveform with only one peak. Thus, this letter proposes a Gaussian inflection point selection method (GIPS). The method uses the number of inflection points (IPs) near the peak of the echo signal to judge the position of waveform half-width and selects an appropriate waveform half-width to iteratively decompose the echo signal to obtain Gaussian components, which are combined into a Gaussian model. Finally, a global Levenberg–Marquardt least-square algorithm (LM algorithm) is used to optimize the Gaussian model for fitting the echo signal. To verify the accuracy and effectiveness of GIPS, the experiments were conducted using land, vegetation and ice sensor (LVIS) data. The results show that the GIPS method can decompose complex LiDAR echo signals more correctly and efficiently than other methods do with an average$R^{2}$of 0.9799.

In the research and development of the coastal ocean, the data of coastal water depth is very important. At present, the development of multispectral satellite water depth measurement is very rapid. In the actual water depth inversion, single-band method, double band method (ratio logarithm method), and multi-band method which are belonging to lyzenga's method, and Strumpf's logarithm ratio method, are widely used. But few people make a comparative analysis of these methods and study their differences. This paper uses the landsat8 oil data and multibeam depth data of Weizhou Island in Guangxi, preprocesses the oil data such as land water separation and atmospheric correction, and then retrieve the water depth by single band method, dual-band method(ratio logarithm method), multi-band method and Strumpf's logarithm ratio method, and uses standard deviation and R2 to evaluate the results of retrieving the water depth.

Using the penetration of blue-green band (532 nm) laser in seawater, airborne laser scanning ranging technology can be applied to shallow sea measurements. The penetration properties of lasers due to the complex optical properties of seawater are also limited. The decrease of echo energy received by the sensor will greatly limit the accuracy of laser seabed survey. In response to this phenomenon, we propose a new structural design method combined with the optimal field of view (FOV) for shallow sea measurements to optimize the traditional receiving system to improve the laser receiving depth echo signal receiving capability. The simulation experiment is carried out by ZEMAX optical software. Experimental results show that the improved receiving system can effectively reduce spherical aberration and coma caused by spherical lens, and improve the imaging quality of the receiving system and the measurement accuracy of the shallow seabed.

At present, APD (Avalanche Photo Diode) arrays LIDAR (Light Detection and Ranging) has been broadly accepted as an important means to obtain 3D (Three Dimensional) data. A new method of a scalable adaptive N × N channel communication system is introduced in the paper, which is aimed at improving the transmission rate of APD array LIDAR data. This paper presents the research on multi-channel communication system based on FPGA (Field Programmable Gate Arrays) configuration, which can be realized multi-channel parallel data independent receiving and transmitting. The multi-channel transmission system not only improves the data bandwidth, but also improve the load capacity of the system. The feasibility of multi-channel communication is verified sufficiently in the paper.

The traditional ortho-rectification technique for remotely sensed imagery, which is performed on the basis of ground image processing platform, has been unable to meet the timeliness requirements. To solve this problem, this paper presents the research on ortho-rectification technique based on field programmable gate array (FPGA) platform, which can be implemented onboard and spaceborne for a real-time processing. Through comparing the correction accuracy and the consuming time of traditional ortho-rectification method with the proposed method based on FPGA, it is demonstrated that the proposed FPGA-based onboard orthorectification has great advantage over improving the image ortho-rectification speed and can reach the requirements of correction accuracy.

In this paper a new way of timing discrimination to measure the timing point of echo signal in pulsed laser rangefinder is presented. This method is an improvement program of high-pass filter scheme. With multiple differential processing of pulsed laser echo signal through high-pass filter circuit, the timing point of laser echo signal will multiple forward approximately. The final identification time and the echo signal which rise along the time interval of initial point will be reduced to the minimum degree, and improve the overall accuracy of the results for a pulsed laser rangefinder, which will eventually minimize walk error between the timing point of the echo signal with the actual beginning timing point of the echo signal and improve precision of the results overall pulse laser radar rangefinding. In addition, the laser echo signal with a small distortion can be still measured and obtained the starting point of the leading edge. Finally, the experimental results show that the proposed new method can reduce the walk error caused by the time delay of the echo pulse timing discrimination, and can also deal with the distorted signal effectively.

Since conventional decision tree (DT) induction methods cannot efficiently take advantage of geospatial knowledge in the classification of remotely sensed imagery, a co-location decision tree (CL-DT) method, combining the co-location technique with the conventional DT method, has been proposed by several researchers. However, the CL-DT method only considers the Euclidean distance of neighborhood events, which cannot truly reflect the co-location relationship between instances for which there is a nonlinear distribution in a high-dimensional space. For this reason, this paper develops the theory and method for a maximum variance unfolding (MVU)-based CL-DT method (known as MVU-based CL-DT). The presented method has been validated by classifying remote sensing image and is compared with CL-DT method and random forest (RF) method. The experimental results show that the proposed method can better construct decision tree and reach a high classification accuracy.

Although many efforts have been made on the fusion of Light Detection and Ranging (LiDAR) and aerial imagery for the extraction of houses, little research on taking advantage of a building's geometric features, properties, and structures for assisting the further fusion of the two types of data has been made. For this reason, this paper develops a seamless fusion between LiDAR and aerial imagery on the basis of aspect graphs, which utilize the features of houses, such as geometry, structures, and shapes. First, 3-D primitives, standing for houses, are chosen, and their projections are represented by the aspects. A hierarchical aspect graph is then constructed using aerial image processing in combination with the results of LiDAR data processing. In the aspect graph, the note represents the face aspect and the arc is described by attributes obtained by the formulated coding regulations, and the coregistration between the aspect and LiDAR data is implemented. As a consequence, the aspects and/or the aspect graph are interpreted for the extraction of houses, and then the houses are fitted using a planar equation for creating a digital building model (DBM). The experimental field, which is located in Wytheville, VA, is used to evaluate the proposed method. The experimental results demonstrated that the proposed method is capable of effectively extracting houses at a successful rate of 93%, as compared with another method, which is 82% effective when LiDAR spacing is approximately 7.3 by 7.3 ft2. The accuracy of 3-D DBM is higher than the method using only single LiDAR data.

This paper presents a new generation of scannerless laser radar measurement system, called GLidar in our project. This system does not require the scanning device; as a result, the dimension of the entire measuring system is small, lightweight, and reliability. The proposed scannerless LiDAR system is especially designated for a small civil UAV platform under a low altitude operation. This paper presents the principle of the array LiDAR imaging, mathematical models of calculating the 3-D coordinates of the laser radar footprints with respect to a mapping coordinate system. Some simulated results are presented on the basis of a test field located in Virginia Wytheville, USA. The simulated results demonstrated that the designated new generation of array LiDAR can achieve 0.06–0.10 m in flat area, 0.31–0.62 m in the edge of house, and 1.23–1.78 m in the forested area compared to an existing DSM data.