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 (DAQ) 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.

Previous control methods developed by our research team cannot satisfy the high accuracy requirements of unmanned surface vessel (USV) path-tracking during bathymetric mapping because of the excessive overshoot and slow convergence speed. For this reason, this study developed an adaptive fuzzy integral-derivative line-of-sight (AFIDLOS) method for USV path-tracking control. Integral and derivative terms were added to counteract the effect of the sideslip angle with which the USV could be quickly guided to converge to the planned path for bathymetric mapping. To obtain high accuracy of the look-ahead distance, a fuzzy control method was proposed. The proposed method was verified using simulations and outdoor experiments. The results demonstrate that the AFIDLOS method can reduce the overshoot by 79.85%, shorten the settling time by 55.32% in simulation experiments, reduce the average cross-track error by 10.91% and can ensure a 30% overlap of neighboring strips of bathymetric LiDAR outdoor mapping when compared with the traditional guidance law.

Previous control methods developed by our research team cannot satisfy the high-accuracy requirements of unmanned surface vessel (USV) path-tracking during bathymetric mapping because of the excessive overshoot and slow convergence speed. For this reason, this study developed an adaptive fuzzy integral-derivative line-of-sight (AFIDLOS) guidance law for USV path-tracking control. Integral and derivative terms were added to counteract the effect of the sideslip angle, with which the USV could be quickly guided to converge to the planned path for bathymetric mapping. To obtain a high-accuracy of the look-ahead distance, a fuzzy control method was proposed. The proposed method was verified using simulations and outdoor experiments. The results demonstrate that the AFIDLOS guidance law can reduce the overshoot by 79.85%, shorten the settling time by 55.32% in simulation experiments, and reduce the average cross-track error by 10.91%, and can ensure a 30% overlap of neighboring strips of bathymetric LiDAR outdoor mapping when compared with the traditional method.