Anti-interrupted-sampling repeater jamming method based on frequency agility waveform and sparse recovery

Abstract Interrupted-sampling repeater jamming (ISRJ) is a type of intra-pulse coherent jamming that poses a significant threat to radar detection and tracking of targets. This paper proposes an ISRJ suppression method based on frequency agile waveform and sparse recovery, starting from the temporal discontinuity and modulation characteristics of ISRJ. This method is particularly suitable for scenarios with high jamming duty ratio (JDR) and high jammer sampling duty ratio (SDR). By dividing the transmitted waveform into sub-pulses with different carrier frequencies and applying a two-round block sparse algorithm, the method accurately recovers three parameters of ISRJ, achieving effective jamming identification, reconstruction, and cancellation. Additionally, a target detection technique based on robust sparse recovery is proposed, significantly improving the stability and accuracy of target detection. Comparative experimental results conducted in three scenarios confirm the effectiveness and superiority of this method under high JDR and SDR conditions

Multiple Mainlobe Interferences Suppression Based on Eigen-Subspace and Eigen-Oblique Projection

When the desired signal and multiple mainlobe interferences coexist in the received data, the performance of the current mainlobe interference suppression algorithms is severely challenged. This paper proposes a multiple mainlobe interference suppression method based on eigen-subspace and eigen-oblique projection to solve this problem. First, use the spatial spectrum algorithm to calculate interference power and direction. Next, reconstruct the eigen-subspace to accurately calculate the interference eigenvector, then generate the eigen-oblique projection matrix to suppress mainlobe interference and output the desired signal without distortion. Finally, the adaptive weight vector is calculated to suppress sidelobe interference. Through the above steps, the proposed method solves the problem that the mainlobe interference eigenvector is difficult to select, caused by the desired signal and the mismatch of the mainlobe interference steering vector and its eigenvector. The simulation result proves that our method could suppress interference more successfully than the former methods

Multicascaded Feature Fusion-Based Deep Learning Network for Local Climate Zone Classification Based on the So2Sat LCZ42 Benchmark Dataset

A detailed investigation of the microclimate is beneficial for optimizing the urban inner/spatial pattern to enhance thermal comfort or even reduce heatwave disasters, whereas accurately classifying local climate zones (LCZs) severely restricts analysis of thermal characterization. Generally, deep learning-based approaches are effective for adaptive LCZ mapping, yet they often have poor accuracy because inadequate cascade feature extraction patterns may not adapt to the fuzzy LCZ boundaries produced by intricate urban textures, especially when using large-scale datasets. To address these issues, we propose a novel CNN model in which we design a strategy that incorporates a triple feature fusion pattern to enhance LCZ recognition based on the So2sat LCZ 42 large-scale annotated dataset. The approach connects multilayer cascaded information to participate in category judgment, which avoids the loss of effective feature information via continuous cascade transformation as much as possible. The results show that the overall accuracy and kappa coefficient of the proposed model reach 0.70 and 0.68, respectively, manifesting an improvement of approximately 4.47% and 6.25% over advanced LCZ classification approaches. In particular, the accuracy of the proposed approach improves even further after the fusion structure or layer depth is partially removed or reduced, respectively. Finally, we discuss several items, including the effectiveness of different parameters and cascaded feature fusion patterns, the superiority of multilayer cascade feature fusion, the mapping impact of seasons and cloud cover, and even some other issues in LCZ mapping. This article will facilitate improvements in the research precision of urban thermal environments

Thermodynamic study of imidazolium halide ionic liquid–water binary systems using excess Gibbs free energy models

In this work, the excess Gibbs free energy models, i.e., non-random two-liquid (NRTL) model and electrolyte NRTL model, including the original one and those with new strategies (association or hydration), were used to describe the macroscopic properties and interpret the microstructure of ionic liquid (IL) - H2O binary systems, clarifying the role of IL association and ion hydration in model development. To provide systematic data for model development, the enthalpy of mixing of three imidazolium-based IL-H2O systems containing the same cation but different sizes of anions, i.e., Cl−, Br−, and I−, were measured. The models were developed and evaluated based on the newly measured data and the osmotic coefficient from the literature. The results reveal that the model reflecting the intrinsic mechanism of dissociation and hydration gives the best modeling results; and the ionic strength and the degree of IL dissociation as a function of water content can be predicted using the newly established model. The study clarifies the significance of IL association and anion hydration in model development and quantitatively demonstrates how water content influences the microstructure and real species in IL-H2O systems.Validerad;2023;Nivå 2;2023-11-23 (hanlid);Funder: National Natural Science Foundation of China (21838004); Joint Research Fund for Overseas Chinese Scholars and Scholars in Hong Kong and Macao Young Scholars (21729601);Full text license: CC BY</p

Experiment and Numerical Study on Deformation Measurement of Cast-in-Place Concrete Large-Diameter Pipe Pile Using Optical Frequency Domain Reflectometer Technology

The Cast-in-place concrete large-diameter pipe (PCC) pile has been used as the foundation reinforcement and embankment in China due to its low cost and high bearing capacity. The deformation of PCC pile under different vertical loads is very important for the application of engineering. In order to study the deformation characteristics of PCC pile, a small-scale model test was carried out. The new distributed measuring technology, named Optical Frequency Domain Reflectometer (OFDR), was applied to measure the strain on the PCC pile. A single mode fiber (SMF) was used, and the methods of layout, packaging and protection of optical fiber are introduced in detail. The obtained data was dealt with by wavelet transform, and the strain curves were analyzed based on the experiments. The finite element (FE) analysis model was established by COMSOL Multiphysics, and the numerical results compared with the experiment results. It showed that the optical fiber sensor can measure the strain of PCC pile, and that the deformation of PCC pile can be successfully obtained by OFDR technology. The strain of the pile decreases with depth and increases with loading. The measured result agrees well with numerical simulation result. The potential application of OFDR technology to PCC pile in situ and PCC energy pile is discussed

Voice over the Dins: Improving Wireless Channel Utilization with Collision Tolerance

Packet corruption caused by collision is a critical problem that hurts the performance of wireless networks. Conventional medium access control (MAC) protocols resort to collision avoidance to maintain acceptable efficiency of channel utilization. According to our investigation and observation, however, collision avoidance comes at the cost of miscellaneous overhead, which oppositely hurts channel utilization, not to mention the poor resiliency and performance of those protocols in face of dense networks or intensive traffic. Discovering the ability to tolerate collisions at the physical layer implementations of wireless networks, we in this paper propose Coco, a MAC protocol that advocates simultaneous accesses from multiple senders to a shared channel, i.e., optimistically allowing collisions instead of simply avoiding them. With a simple but effective design, Coco addresses the key challenges in achieving collision tolerance, such as precise sender alignment and fine control of the transmission concurrency. We implement Coco in 802.15.4 networks and evaluate its performance through extensive experiments with 21 TelosB nodes. The results demonstrate that Coco is light-weight and enhances channel utilization by at least 20% in general cases, compared with state-of-the-arts protocols

Two-Dimensional PC-SAFT-DFT Adsorption Models for Carbon Slit-Shaped Pores with Surface Energetical Heterogeneity and Geometrical Corrugation

Studying the effects of surface curvature and energetic heterogeneity on adsorption on carbon surfaces has aroused great interest. Utilizing the PC-SAFT-DFT model may be a promising approach for it. However, efficient algorithms are needed to obtain the two-dimensional (2D) PC-SAFT-DFT calculation results efficiently. In this work, first, the Chebyshev pseudospectral collocation method was extended to 2D PC-SAFT-DFT calculation with complex boundary conditions. In addition, an efficient approach to calculate the matrices required in the Chebyshev pseudospectral collocation method has been proposed which significantly reduces the computation time. Based on the accelerated PC-SAFT-DFT program, a preliminary study of the effects of the surface curvature and energetic heterogeneity for pure and mixed gas adsorption was conducted