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Trajectory prediction (TP) of ballistic missile (BM) is a critical task in the field of military and defense security. However, influenced by various external factors, including target maneuverability, interference, and atmospheric conditions, BMs encounter complex forces during the boost flight phase, making their trajectories complex and variable. Furthermore, the conventional numerical integration and polynomial fitting TP methods are highly dependent on fixed motion models and precise initial observations, so they tend to engender error accumulation and inaccurate predictions. Thus, in terms of this issue, this paper proposed a TP method based on adaptive tracking and Gaussian Process Regression (GPR) to achieve stability in short-term TP for boost phase BM. Specifically, a database of trajectories for boost phase BM is created and used for training GPR predictive models, in which the unknown noise's covariance matrix is dynamically adjusted according to the statistical characteristics of observations to provide more precise trajectory data for model training. At the same time, incremental learning is adopted to add tracking results from real-time tests to improve further and update the predictive model. Additionally, the output uncertainty of GPR is also beneficial for decision-making systems usually making decisions in accordance with the uncertainty. Simulation results based on the GEO dual-satellite positioning system show that the absolute average TP RMSE of the boost phase BM of our proposed method can be less than 0.35 km, 0.51 km, and 0.62 km in future 20 s, 40 s, and 60 s, which outperforms those of the numerical integration method of 2.1 km, 3.7 km, and 6.9 km and the function approximation method of 0.89 km, 3.1 km, and 6.1 km. This paper provides a significant reference for the positioning, tracking, and prediction of BM in boost phase.

Although the thermal infrared remote sensing camera plays a pivotal role in Earth observation, and impacts the target detection, surface temperature inversion, and subsequent space missions significantly, the imaging quality of the camera is constrained by its optics, image sensors, and electronics during on-orbit operation. At the same time, the traditional blind recovery algorithms, which require extensive time for estimating intricate blur kernels, encounter challenges due to varying atmospheric conditions and other factors leading to dissimilar blur kernels across different observation scenes. In this context, this article introduces a rapid image recovery algorithm rooted in the concept of the invariant modulation transfer function (IMTF) specific to on-orbit cameras. The IMTF model remains stable and impervious to influences stemming from ground targets, atmospheric conditions, and orbital or environmental fluctuations, contingent upon the camera’s inherent characteristics. The extraction of the IMTF involves subjecting the transfer function’s region to a modified edge methodology, followed by image recovery through a hyper-Laplacian prior inverse convolution approach. The resolution of the inverse problem is achieved by employing an alternating minimization scheme. This method addresses the mitigation of imaging artifacts originating from the camera’s limitations. Comparative analysis against the state-of-the-art image recovery techniques establishes the competitiveness of the method proposed in this article, both in terms of recovery efficacy and operational efficiency. Substantiating this, experimental validation using in-orbit thermal infrared remote sensing images reveals a notable improvement in the average gradient (AG) (by a factor of 3.2), edge intensity (EI) (by a factor of 2.5), and modulation transfer function (by a factor of 1.3) of the restored images. Consequently, this approach introduces a novel perspective for enhancing the restoration of in-orbit remote sensing images.

This study aims to identify the difference in the mobilisation degree of RAP asphalt binder under three mixing techniques and its influences on the performance of recycled hot-mix asphalt mixture (HMA). Glass beads were selected to replace parts of fresh coarse aggregates, and to analyze the transfer of RAP binder using Fourier Transformation Infrared (FTIR) spectroscope analysis. Superpave Gyratory Compactor (SGC) and Hamburg Wheel-Track Device (HWTD) were used to evaluate the compaction property and the high-temperature performance of recycled HMA. Results showed that the relative percentage of reclaimed asphalt recovered (Rp) varied with the mixing techniques. The workability of recycled HMA is related to the mixing technique. The softer fresh asphalt binder is more capable of facilitating the mineral aggregates to form a stable skeleton structure. In addition, the transfer of RAP binder in recycled HMA may be an important factor influencing the skeleton structure.

Acetate-based ice control chemicals have been shown to have less environmental impact compared with traditional de-icing salts. However, their impact on the asphalt pavement’s performance has been underestimated and has drawn the attention of pavement engineers. This study was undertaken to evaluate the effect of de-icing chemicals (potassium acetate) and the freeze-thaw cycle on the rutting resistance of asphalt mixtures. Two types of airport pavement mixtures (AS and AB) and three roadway mixtures (HL3, HL3 HS, and HL1) were tested through the Hamburg wheel tracking test (HWTT) under three different treatments for the testing specimens: treated with potassium acetate solution, with one freeze-thaw cycle; and treated with potassium solution and one freeze-thaw cycle, respectively. The results show that potassium acetate solution and the freeze-thaw cycle can significantly affect the rutting resistance of all tested mixtures, and potassium acetate might have the potential to induce stripping damage on asphalt mixtures. A combination of de-icing treatment and the freeze-thaw cycle can potentially mitigate the stiffness compromise caused by their sole impact. Asphalt binder type, asphalt content, and different treatment methods have a statistical effect on the rutting resistance of asphalt mixture applied both on airside and roadway pavements.

Recent rediscovered layered material-black phosphorous with a puckered honeycomb atomic structure has experienced an upsurge in demand owing to its exotic physical properties such as layer-independent direct bandgap and linear dichroism. This Letter presents plasmonic properties of the nanostructured BP flake and its unprecedented capability of wide-band photon manipulation within the deep subwavelength scale. Owing to its anisotropic characteristic in band structure and moderate mobility, a strong layer number and polarization dependences of the plasmon resonance with frequencies ranging from infrared (IR) to terahertz have been found. Oblique plasmons have been observed in the square array of a black phosphorus (BP) flake, with the resonant frequency tuned in-situ, either electrically or optically, plus strong plasmon-induced absorption. Such advantages place BP as the best alternate candidate of plasmonic materials for ultra-scaled optoelectronic integration from terahertz to mid-IR.