Ligang Li

In order to improve the accuracy and robustness of path following control for an Unmanned Surface Vehicle (USV) suffering from unknown and complex disturbances, a variable speed curve path following a control method based on an extended state observer was proposed. Firstly, the effect of the environmental disturbances on the USV is equivalent to an unknown and time-varying sideslip angle, and the sideslip angle is estimated by using the extended state observer (ESO) and compensated in the Line of Sight (LOS) guidance law. Secondly, based on the traditional LOS guidance law, the design of the surge velocity guidance law is added to enable the USV to self-adjust the surge velocity according to the curvature of the curve path, thus further improving the tracking accuracy. Finally, the heading and speed controller of the USV is designed by using a sliding mode control to track the desired heading and speed accurately, and then the path following control of the USV’s curve path is realised. Simulation results verify the effectiveness of the proposed method.

Synthetic aperture radar (SAR) can extract sea surface wind speed information. To extract wind speed information through the geophysical model function (GMF), the corresponding wind direction information must be input. This article introduces some concepts about networked SAR satellites. The networked satellites enable multiple SARs to observe the same sea surface at different incidence angles at the same time. Aiming at the X-band networked SAR data with different incident angles, the cost function is established by using the GMF. By minimizing the cost function, accurate wind speed information can be extracted without inputting wind direction information. When the noise is small, the wind direction information is introduced, and the accuracy of the extracted wind speed will be improved. When the noise is less than 1 dB and the incident angle is greater than 30°, the root-mean-square error (RMSE) of the wind speed extracted by this method is basically less than 2 m/s.

Azimuth cutoff is an inherent disadvantage of synthetic aperture radar (SAR) wave observation. The waves shorter than some certain wavelength (azimuth cutoff) cannot be imaged in original form (structures) by SAR. For a single SAR observation, the problem of the azimuth cutoff for ocean waves can be resolved to some extent by cooperative observations of SAR satellites. Multiple SAR satellites are required to achieve simultaneous observation of an ocean area to obtain multiview SAR ocean wave synchronization data. Currently, these data cannot be acquired from in-orbit SARs. In this study, imaging simulations of multiview SAR ocean wave synchronization data based on small SAR satellites were carried out for the first time with X-band, 4-m resolution, stripmap mode and Single Look Complex (SLC) product. The Max Planck Institute (MPI) method was used to obtain the optimum wave spectrum of the synchronous data. The influencing factors of the azimuth cutoff wavelength were analyzed by using measured and simulated SAR data. The analysis results were used to develop a novel multiview wave spectrum data fusion method for azimuth cutoff compensation. The azimuth cutoff compensation effect was evaluated by comparing the inversion results before and after data fusion: the azimuth cutoff decreased by 9.76% on average, the root mean square error (RMSE) of the significant wave height is 0.06m, and RMSE of the mean wave period is 0.58s. The azimuth cutoff compensation method can be applied to SAR data for medium and low sea states (that is, wind speeds of 5-15 m/s). These results show that the proposed method of multiview wave spectrum data fusion effectively compensates for azimuth cutoff.

Due to the nonlinear effect of velocity bunching modulation, azimuth cutoff occurs when waves are propagating along the azimuth direction. This is an inherent disadvantage of synthetic aperture radar (SAR) wave observation and makes it impossible to obtain complete wave information. For a single SAR observation, the problem of the azimuth cutoff wavelength of ocean waves can be solved to some extent by the cooperative observations of SAR satellites. It is necessary to use multiple SAR satellites to achieve simultaneous observation of the same ocean area to obtain multiview SAR ocean wave synchronization data. At present, it is impossible to acquire multiview synchronization data based on in-orbit SARs. Therefore, this paper first carried out imaging simulations of multiview SAR ocean wave synchronization data. Second, the MPI method was used to obtain the optimum wave spectrum of synchronous data. The influencing factors of the azimuth cutoff wavelength were analyzed by using the measured SAR data. Based on the analysis results, a new method of multiview wave spectrum data fusion is proposed to realize azimuth cutoff compensation. The azimuth cutoff compensation effect is evaluated by using the inversion results of the azimuth cutoff before and after spectral data fusion, the significant wave height and the mean wave period. The results show that the azimuth cutoff compensation method established in this paper can solve the problem of information loss caused by azimuth cutoff to some extent, improve the ability of SAR wave observation, and lay a foundation for SAR wave operational observation.