This paper proposes a novel formation control strategy for nonholonomic intelligent vehicles based on virtual structure and consensus approach. The formation model is obtained based on the coordinate transformation and the virtual structure technique. The controllers are designed by using nonholonomic target tracking technique and leader-following consensus protocol. Depending on virtual structure approach and coordinate transformation, the formation control problem of multiple nonholonomic intelligent vehicles is converted into the target tracking and state consensus stabilization problem. Simulation and real-world experimental results show the correctness and effectiveness of the strategy

Synthetic aperture radar (SAR) is an important means to observe the sea surface wind field. Sentinel-1 and GF-3 are located on orbit SAR satellites, but the SAR data quality of these two satellites has not been evaluated and compared at present. This paper mainly studies the data quality of Sentinel-1 and GF-3 SAR satellites used in wind field inversion. In this study, Sentinel-1 SAR data and GF-3 SAR data located in Malacca Strait, Hormuz Strait and the east and west coasts of the United States are selected to invert wind fields using the C-band model 5.N (CMOD5.N). Compared with reanalysis data called ERA5, the root mean squared error (RMSE) of the Sentinel-1 inversion results is 1.66 m/s, 1.37 m/s and 1.49 m/s in three intervals of 0~5 m/s, 5~10 m/s and above 10 m/s, respectively; the RMSE of GF-3 inversion results is 1.63 m/s, 1.45 m/s and 1.87 m/s in three intervals of 0~5 m/s, 5~10 m/s and above 10 m/s, respectively. Based on the data of Sentinel-1 and GF-3 located on the east and west coasts of the United States, CMOD5.N is used to invert the wind field. Compared with the buoy data, the RMSE of the Sentinel-1 inversion results is 1.20 m/s, and the RMSE of the GF-3 inversion results is 1.48 m/s. The results show that both Sentinel-1 SAR data and GF-3 SAR data are suitable for wind field inversion, but the wind field inverted by Sentinel-1 SAR data is slightly better than GF-3 SAR data. When applied to wind field inversion, the data quality of Sentinel-1 SAR is slightly better than the data quality of GF-3 SAR. The SAR data quality of GF-3 has achieved a world-leading level.

The paper studies the time-invariant formation problem of second-order multi-agent systems under a time-invariant directed communication topology. Extensions of the consensus protocol are introduced in the formation control. By choosing appropriate consensus states, the state-linear-transformation approach and the partial stability theory are adopted to analyze the formation problem. Sufficient and necessary algebraic criteria are derived for the formation regulation problem with or without velocity constrains and the formation tracking problem. They are expressed in terms of Hurwitz stability of matrices which are constructed from the gain matrices of formation control protocols.

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.