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This paper considers the problem of multiple missiles to attack a maneuvering target simultaneously. Based on a fixed-time fast nonsingular terminal sliding mode surface (FNTSMS), fixed-time distributed cooperative guidance laws are developed. By designing guidance laws along and perpendicular to line of sight (LOS) direction, both relative velocity and range-to-go are consistent. In addition, a saturation function is introduced to avoid the chattering problem caused by the commonly used sign function. Furthermore, a distributed cooperative guidance law with communication failure is considered and proved theoretically, which shows that the proposed guidance law has excellent performance. Finally, the simulation results not only explain the performance of the distributed guidance law,but also verify the robustness against communication topology switching. [ABSTRACT FROM AUTHOR]

Revealing the land subsidence in Beijing, China, induced by the massive groundwater extraction in the past three decades, is important to mitigate the hazards and protect the residences and infrastructure. Many SAR (Synthetic Aperture Radar) datasets have been successfully applied to reveal the land subsidence over Beijing in previous research, while few works were achieved on land subsidence revealed by time-series InSAR (Interferometric Synthetic Aperture Radar) with Gaofen-3 SAR images. In this study, we successfully perform the time-series InSAR analysis with Gaofen-3 SAR images to extract the land subsidence in Beijing from 2020 to 2021. The Sentinel-1 SAR images were used to assess the accuracy of Gaofen-3 images. The subsidence scale and extent are consistent in detected major subsidence bowls between the two datasets. The spatial–temporal evolution and the deceleration of Beijing land subsidence were revealed by comparing with the Sentinel-1 results from 2017 to 2020. Moreover, we evaluated the interferometric performance of Gaofen-3 satellite SAR imagery and analyzed the main factors that mostly influence the coherence and quality of interferograms. Our results proved that the long perpendicular baselines decrease the coherence seriously over the study area, and the artifacts induced by inaccurate orbit information reduce the quality of the Gaofen-3 interferograms. Refining and removing the two main artifacts could improve the quality of interferograms formed by Gaofen-3 SAR images. [ABSTRACT FROM AUTHOR]

Landslides are a major concern in the mountainous regions of southwest China, leading to significant loss of life and property damage. Therefore, it is crucial to identify potential landslides for early warning and mitigation. stacking-InSAR, a technique used for landslide identification in a wide area, has been found to be faster than conventional time-series InSAR. However, the dense vegetation in southwest China mountains has an adverse impact on the coherence of stacking-InSAR, resulting in more noise and inaccuracies in landslide identification. To address this problem, this paper proposes an improved seasonal interferometry stacking-InSAR method. It uses Sentinel-1 satellite data from 2017 to 2022. The study area is the river valley section of the G213 road from Wenchuan County to Mao County. The study reveals the characteristics of seasonal decoherence in the steep mountainous region, and identifies a total of 21 potential landslides using the improved method. Additionally, optical satellite imagery and LiDAR data were used to assist in the identification of potential landslides. The results of the conventional stacking-InSAR method and the improved seasonal interferometry stacking-InSAR method are compared, showing that the latter is more effective in noise suppression caused by low coherence. Their standard deviations were reduced by 46%, 22%, 10%, and 14%, respectively, using the quantitative statistics for the four tested areas. The proposed method provides an efficient and effective approach for detecting potential landslides in the mountainous regions of southwest China. It can serve as a valuable technical reference for future landslide identification studies in this area. [ABSTRACT FROM AUTHOR]

The Guest Editors and the Publisher have retracted this article. This paper has been formally retracted from publication by the authors on ethical grounds. Actually, one of the authors (Mr. Peilian Ran) neglected that a similar paper was already presented and published in a previous conference proceedings. The authors are responsible for this mistake and apologise for it. Request approved by the proceedings Editor and the Publisher on February 2, 2021.

Beijing is one of the largest cities in China, which has suffered from land subsidence for a long time. According to the study from 2005 to 2017, the maximum subsidence rate of Beijing is more than 10 cm/year. This paper will use Sentinel-1A TOPS data for the first time to reveal the land subsidence of Beijing from 2017 to 2018 by using time series interferometry. SBAS-InSAR technology was used for time series analysis. The annual mean subsidence rate and time series subsidence of Beijing were obtained. The results show that the east of Chaoyang district and the northwest of Tongzhou district were the severe subsidence areas in Beijing, and the subsidence rate is more than 10 cm/year, which indicates that the subsidence area in Beijing is continuous in recent years, and corresponding measures should be taken by the government.

A triboelectric nanogenerator (TENG) facilitates the advancement of self‐powered displacement sensors, which are important for many autonomous intelligent microsystems. However, the amplitude‐based displacement sensing of conventional TENG‐based sensors still suffers significantly from varying charge densities in harsh environments. Benefiting from the combination of intelligent signal processing algorithms and direct‐current TENG sensors, this study proposes an environmentally robust character‐based displacement sensing method that eliminates the influences of varying charge density in principle. The experimental results show that under drastically changing air humidity and other harsh environments, the sensing of threshold and maximum displacement has far superior consistency and stability than that of traditional amplitude‐based TENG sensors, providing a novel route to realize reliable self‐powered displacement sensing in environment‐variable applications. [ABSTRACT FROM AUTHOR]

Electricity is the basic and essential need for every single person and guarantees the development of society, industry, and the economy. The limited conventional fossil fuel meets the challenge of the sharply increasing demand, while may lead to severe pollution. Emerging green energy harvesting systems can convert ambient kinetic, thermal, and solar energy to electricity effectivity. In this review paper, the authors provide an overview of the new and emerging methods, droplet‐based electricity generators, that convert energy from the ubiquitously existing water droplets. The authors begin with a brief introduction of the working principle for droplet‐based power generators. Existing configurations of the droplet‐based power generator are also summarized, including 1) single electrode, 2) transistor‐based, and 3) direct current generator. Then, a detailed discussion of the design and operation factors that may impact the energy harvesting efficiency of droplet‐based power generators is provided. Hybrid energy harvester that integrates droplet‐based power generators with other triboelectric, pyroelectric, and photovoltaic‐based devices are summarized. Finally, challenges and perspectives regarding the future development of droplet‐based power generators are described. The reviews demonstrate a highly efficient method for energy harvesting from water droplets to meet the vital needs of the energy crisis. [ABSTRACT FROM AUTHOR]