Search Results (30)

A primary objective of this research entails the development of an innovative algorithm capable of tracking a drone in real-time. This objective serves as a fundamental requirement across various applications, including collision avoidance, formation flying, and the interception of moving targets. Nonetheless, regardless of the efficacy of any detection algorithm, achieving 100% performance remains unattainable. Deep neural networks (DNNs) were employed to enhance this performance. To facilitate real-time operation, the DNN must be executed within a Deep Learning Processing Unit (DPU), Neural Processing Unit (NPU), Tensor Processing Unit (TPU), or Graphics Processing Unit (GPU) system on board the UAV. Given the constraints of these processing units, it may be necessary to quantify the DNN or utilize a less complex variant, resulting in an additional reduction in performance. However, precise target detection at each control step is imperative for effective flight path control. By integrating multiple algorithms, the developed system can effectively track UAVs with improved detection performance. Furthermore, this paper aims to establish a versatile Unmanned Aerial System (UAS) development platform constructed using open-source components and possessing the capability to adapt and evolve seamlessly throughout the development and post-production phases. Full article

The hydrocyclone generally exhibits limited separation efficiency and classification sharpness. As the discharge channel for fine particles, the vortex finder plays a critical role in influencing the classification performance through its structural parameters. However, the influence of vortex finder wall thickness on fly ash classification within the hydrocyclone has not yet been reported. In this study, computational fluid dynamics (CFDs) were employed to investigate the variations in pressure field, velocity field, and separation efficiency with respect to changes in vortex finder wall thickness. The results indicate that the radial velocity increases with vortex finder wall thickness, which facilitates the rapid formation of a particle-size stratification, thereby reducing the number of misclassified particles. The cut size initially decreases and then increases as the wall thickness of the vortex finder increases. A minimum cut size of 17.2 µm was observed when the wall thickness reached 10 mm. The classification sharpness improves progressively with increasing wall thickness. At a wall thickness of 15 mm, the steepness index reaches 0.68. Experimental results demonstrate that a thick-walled vortex finder structure can significantly enhance the classification sharpness of the hydrocyclone. Specifically, the content of −19 µm particles in the underflow decreased by 32.17% when the vortex finder wall thickness increased from 5 mm to 15 mm. Meanwhile, the proportion of −19 µm particles in the overflow increased by 12.72%. Therefore, employing a thick-walled vortex finder structure can not only enhance the cut size precision but also effectively improve the classification performance of the hydrocyclone. Full article

Satellite formation flying faces significant challenges in maintaining its desired configurations due to various orbital perturbations, particularly in low-Earth-orbit environments. This paper presents a novel approach to generating fuel-optimal reference trajectories for in-track satellite formations by incorporating both the Earth’s oblateness ($J_2$ perturbation) and the inherent nonlinearity of the two-body problem. The resulting indirect optimal control problem is solved using Pontryagin Neural Networks (PoNNs). The proposed method transforms the conventional two-point boundary value problem into a mathematical programming problem, enabling the efficient computation of optimal trajectories. The effectiveness of our approach is validated through extensive numerical simulations at different inclinations of the chief satellite (0–90°) and cross-track separation distances (1–400 km), demonstrating significant reductions in annual fuel consumption compared to conventional approaches. The feasibility of these optimal trajectories is verified through closed-loop simulations using a PD controller, confirming their practical applicability in realistic mission scenarios. This research contributes to enhancing the long-term sustainability of satellite formation flying missions by optimizing fuel efficiency while maintaining precise formations. Full article

Polyimide (PI) with surface microstructures has broad application prospects in aerospace, integrated circuits, and optical engineering due to its excellent mechanical properties, high thermal stability, and chemical resistance. Ultra-precision fly-cutting (UPFC) is a promising advanced technique for machining PI microstructures. However, few studies on the UPFC of PI materials are reported. In this study, the machining principle of UPFC is analyzed, and a comparative study of different processing strategies is conducted. The experimental results demonstrate that the climb cutting strategy is more suitable for PI microstructure machining, which can significantly reduce burr formation and achieve lower surface roughness. The theoretical models describing tool motion and predicting maximum chip thickness in UPFC are established, and the predicted chip thickness is consistent with the experimental results. Moreover, the influence of process parameters on the surface morphology and dimensional accuracy of microstructures is assessed through a series of experiments. The results indicate that cutting depth and step-over are the dominant factors influencing dimensional accuracy and surface roughness. Furthermore, the cutting force during UPFC is extremely small, only in the range of millinewtons (mN). In addition, the cutting force in the feed direction exhibits a high sensitivity to variations in process parameters compared to other directional components. This study provides theoretical guidance for the establishment of a theoretical model and the selection of UPFC process parameters for fabricating PI microstructures. Full article

The high-repetition-rate dual-microcomb interferometry, characterized by its high precision, rapid measurement speed, and ease of integration, shows significant promise in applications such as precision spectroscopy and high-speed precision ranging. As dual-microcomb interferometry usually requires a specific difference in repetition rates, tuning the repetition rate of the microcomb is crucial for integrating dual-microcomb sources and enhancing the measurement performance, including the precision and the update rate. This work demonstrates a coherent dual-microcomb system driven by a single continuous-wave fiber laser at 1560.49 nm. The system employs a hybrid tuning method combing single-sideband (SSB) modulation for precision pump frequency control (enabling continuous repetition rate tuning across a 4.34 MHz range) with thermal control for coarse tuning. The linear dependence between the repetition rate and pump modulation frequency shows a measured coefficient of 143.58 kHz/GHz. This method enables dual microcombs with MHz-level repetition rate tuning, significantly relaxing the fabrication and pairing requirements for microresonators. The advancement is particularly valuable for dual-comb spectroscopy and ranging applications, including gas detection and satellite formation flying. Full article

Colorectal cancer is one of the most common malignant tumors worldwide, significantly impacting human health. Cantharidin (CTD), an active compound derived from the Spanish fly, exhibits antitumor properties. Its derivative, norcantharidin (NCTD), is synthesized by removing methyl groups from positions 1 and 2 of cantharidin. NCTD has demonstrated lower toxicity while maintaining similar antitumor effects compared to CTD. However, the mechanism by which NCTD exerts its effects against colorectal cancer remains unclear. Here, we conducted a comprehensive analysis of the effects of NCTD on colorectal cancer both in vitro and in vivo. Whole-transcriptome sequencing and bioinformatics tools were employed to identify potential key targets of NCTD in the treatment of colorectal cancer. Additionally, we designed folate-receptor-targeting NCTD liposomes (FA-NCTD) and assessed their anticancer efficacy in vivo. NCTD effectively inhibited cell viability, clonal formation, and migration in HCT116 and HT-29 cell lines. NCTD also induced apoptosis, influenced the cell cycle, altered mitochondrial membrane potential, and increased reactive oxygen species levels. The whole-transcriptome sequencing and bioinformatics analysis identified TRAF5 as a key target for NCTD’s action against colorectal cancer. Furthermore, NCTD was found to regulate the TRAF5/NF-κB signaling pathway in both HCT116 and HT-29 cells. The FA-NCTD liposomes demonstrated effective tumor targeting and significantly inhibited tumor growth in vivo. This result showed that NCTD effectively suppresses the malignant proliferation of colon cancer cells by modulating the TRAF5/NF-κB signaling pathway and inducing programmed apoptosis, thereby offering a novel strategy for colorectal cancer treatment. The prepared FA-NCTD liposomes provide a promising approach for achieving the precise targeting and controlled release of NCTD. Full article

The PIESAT-01 constellation is the world’s first multi-baseline distributed synthetic aperture radar (SAR) constellation with a “Cartwheel” formation. The “Cartwheel” formation is a unique formation in which four satellites fly in companion orbits, ensuring that at any given moment, the main satellite remains at the center, with three auxiliary satellites orbiting around it. Due to this unique configuration of the PIESAT-01 constellation, four images of the same region and six pairs of baselines can be obtained with each shot. So far, there has been no imaging and interference research based on four-satellite constellation measured data, and there is an urgent need to explore algorithms for the “Cartwheel” configuration imaging and digital surface model (DSM) production. This paper introduces an improved bistatic SAR imaging algorithm under the four-satellites interferometric mode, which solves the problem of multi-orbit nonparallelism in imaging while ensuring imaging coherence and focusing ability. Subsequently, it presents an interferometric processing method for the six pairs of baselines, weighted fusion based on elevation ambiguity from different baselines, to obtain a high-precision DSM. Finally, this paper selects the Dingxi region of China and other regions with diverse terrains for imaging and DSM production and compares the DSM results with ICESat-2 global geolocated photon data and TanDEM DSM data. The results indicate that the accuracy of PIESAT-01 DSM meets the standards of China’s 1:50,000 scale and HRTI-3, demonstrating a high level of precision. Moreover, PIESAT-01 data alleviate the reliance on simulated data for research on multi-baseline imaging and multi-baseline phase unwrapping algorithms and can provide more effective and realistic measured data. Full article

Satellite formation flying technology currently represents a focal point in space mission research. Traditional spacecraft payload performance and lifespan are often constrained by propellant limitations. Electromagnetic Formation Flying (EMFF), a propellant-free formation flying technique, has garnered widespread attention. Its inherent strong nonlinearity and coupling present challenges for high-precision control within EMFF. This paper presents the relative motion dynamics of a two-satellite EMFF in the port-Hamiltonian framework and constructs an accurate nonlinear model of the dynamics. Utilizing the concept of Interconnection and Damping Assignment and nonlinear disturbance observer, a composite disturbance-rejection passivity-based controller is designed, offering a method for controlling the magnetic dipole strength of formation satellites. Finally, numerical simulations are conducted to demonstrate the viability of the proposed dynamics model and control strategy. Full article

Light bending is one of the classical tests of general relativity and is a crucial aspect to be taken into account for accurate assessments of photon propagation. In particular, high-precision astrometry can constrain theoretical models of gravitation in the weak field limit applicable to the Sun neighborhood. We propose a concept for experimental determination of the light deflection close to the Sun in the ${10}^{-7}$ to ${10}^{-8}$ range, in a modern rendition of the 1919 experiment by Dyson, Eddington and Davidson, using formation flying to generate an artificial long-lasting eclipse. The technology is going to be demonstrated by the forthcoming ESA mission PROBA3. The experimental setup includes two units separated by 150 m and aligned to the mm level: an occulter and a small telescope (0.3 m diameter) with an annular field of view covering a region $0^{\circ }.7$ from the Sun. The design is compatible with a space weather payload, merging several instruments for observation of the solar corona and environment. We discuss the measurement conditions and the expected performance. Full article

Hypoxia not only plays a critical role in multiple disease conditions; it also influences the growth and development of cells, tissues and organs. To identify novel hypoxia-related mechanisms involved in cell and tissue growth, studying a precise hypoxia-sensitive time window can be an effective approach. Drosophila melanogaster has been a useful model organism for studying a variety of conditions, and we focused in this study on the life cycle stages of Drosophila to investigate their hypoxia sensitivity. When normoxia-grown flies were treated with 4% O₂ at the pupa stage for 3, 2 and 1 day/s, the eclosion rates were 6.1%, 66.7% and 96.4%, respectively, and, when 4% O₂ was kept for the whole pupa stage, this regimen was lethal. Surprisingly, when our hypoxia-adapted flies who normally live in 4% O₂ were treated with 4% O₂ at the pupa stage, no fly eclosed. Within the pupa stage, the pupae at 2 and 3 days after pupae formation (APF), when treated for 2 days, demonstrated 12.5 ± 8.5% and 23.6 ± 1.6% eclosion, respectively, but this was completely lethal when treated for 3 days. We conclude that pupae, at 2 days APF and for a duration of a minimum of 2 days, were the most sensitive to hypoxia. Our data from our hypoxia-adapted flies clearly indicate that epigenetic factors play a critical role in pupa-stage hypoxia sensitivity. Full article

Serotonin is a monoamine that acts in vertebrates and invertebrates as a modulator promoting changes in the structure and activity of brain areas relevant to animal behavior, ranging from sensory perception to learning and memory. Whether serotonin contributes in Drosophila to human-like cognitive abilities, including spatial navigation, is an issue little studied. Like in vertebrates, the serotonergic system in Drosophila is heterogeneous, meaning that distinct serotonergic neurons/circuits innervate specific fly brain regions to modulate precise behaviors. Here we review the literature that supports that serotonergic pathways modify different aspects underlying the formation of navigational memories in Drosophila. Full article

The prescribed performance robust control method for the leader/follower (L/F) formation is proposed in this paper to solve the problem of spacecraft formation flying (SFF) full-process control (FPC). The objective of FPC is to establish an ultra-close formation with the constraint of collision avoidance between two spacecraft, and then to maintain the formation configuration with high-precision accuracy in a period of time. The main contribution of this paper lies in the following three aspects. Firstly, the six-degree-of-freedom (DOF) error dynamics model of SFF is developed to describe the synchronization motion of the L/F system. Secondly, the prescribed performance bound that comprehensively considers transience and transient performance is designed, which is key for the realization of collision avoidance and high-precision accuracy requirements. Finally, combing prescribed performance control and robust control theories, based on the backstepping method, the predefined performance robust controller is designed, and the tracking errors are proven to converge to the predefined performance bounds in the presence of external disturbances by using the predefined performance robust controller. Illustrative simulations are performed to verify the proposed theoretical results. Full article

Relative pose estimation of a satellite is an essential task for aerospace missions, such as on-orbit servicing and close proximity formation flying. However, the changeable situation makes precise relative pose estimation difficult. This paper introduces a deep-learning-based satellite relative pose estimation method for monocular optical images. The method is geared towards uncooperative target satellites with known 3D models. This paper proposes a novel convolutional neural network combined with 3D prior knowledge expressed by the 3D model in the form of the point cloud. The method utilizes point cloud convolution to extract features from the point cloud. To make the result more precise, a loss function that is more suitable for satellite pose estimation tasks is designed. For training and testing the proposed method, large amounts of data are required. This paper constructs a satellite pose estimation dataset BUAA-SID-POSE 1.0 by simulation. The proposed method is applied to the dataset and shows desirable performance on the pose estimation task. The proposed technique can be used to accomplish monocular vision-based relative pose estimation tasks in space-borne applications. Full article

One of the important applications of the space tethered system is formation flying. To satisfy the requirement for interferometry of ground targets by remote-sensing satellites, a new type of tethered solar sail spacecraft has been proposed in recent research. The replacement of subsatellites of conventional tethered satellite systems with solar sail spacecraft allows for a special formation configuration in which the main satellite is in sun-synchronous orbit and the subsolar sail is in displaced orbit. If the solar sail is at the appropriate attitude, the main satellite and the solar sail spacecraft connected by metal tethers could move side by side, hence this formation system is called transverse formation. The relative baseline of this transverse formation system is perpendicular to the ground trajectory of the satellite, effectively solving the problem that the relative baseline of conventional orbital formations varies in a trigonometric cycle. Researchers on the past ignored the mass and elasticity of the tether, and considered the tether just a constraint in the model system. Since the solar sail is generally quite light compared to the other components of the system, the model inaccuracy caused by ignoring the mass of the tether on the dynamic model and control is extremely obvious. This paper investigates the relative dynamics and control of a proposed system during the deployment process with the mass of the tether. Two precise models of satellite-sail systems are established. One is based on the dumbbell model with the mass tether for the tethered satellite system, and the other is on the basis of the beads model of a tethered satellite system. The rigid one is for control design and the flexible one is for dynamic simulation. It is concluded that the length of the tether and attitude angle of the transverse formation configuration can be decoupled and controlled separately. On the basis of the models, a length rate and LQR control law is developed and the control of the deployment and retrieval process of the tethered solar sail system is investigated. Numerical simulations are performed to verify the accuracy of the conclusions. Full article

Estimation of spacecraft pose is essential for many space missions, such as formation flying, rendezvous, docking, repair, and space debris removal. We propose a learning-based method with uncertainty prediction to estimate the pose of a spacecraft from a monocular image. We first used a spacecraft detection network (SDN) to crop out the rectangular area in the original image where only spacecraft exist. A keypoint detection network (KDN) was then used to detect 11 pre-selected keypoints with obvious features from the cropped image and predict uncertainty. We propose a keypoints selection strategy to automatically select keypoints with higher detection accuracy from all detected keypoints. These selective keypoints were used to estimate the 6D pose of the spacecraft with the EPnP algorithm. We evaluated our method on the SPEED dataset. The experiments showed that our method outperforms heatmap-based and regression-based methods, and our effective uncertainty prediction can increase the final precision of the pose estimation. Full article