RESUMO
The specific emitter identification is widely used in electronic countermeasures, spectrum control, wireless network security and other civil and military fields. In response to the problems that the traditional specific emitter identification algorithm relies on a priori knowledge and has poor generalizability, and the existing specific emitter identification algorithm based on deep learning has poor feature selection and the adopted feature extraction network is not targeted, etc., the specific emitter identification algorithm based on multi-sequence feature learning is proposed. Firstly, multiple sequence features of the emitted signal of the communication radiation source are extracted, and these features are combined into multiple sequence features. Secondly, the multiple sequence fusion convolutional network is constructed to fuse and deeply extract the multiple sequence features and complete the classification of individual communication radiation sources through the classifier of neural network. The selected sequence features of this algorithm contain more and more essential RFF information, while the targeted design of the multi-sequence feature fusion learning network can effectively extract the essential RFF information. The results show that the algorithm can significantly improve the performance of SEI compared with the benchmark algorithm, with a recognition rate gain of about 17%.
Assuntos
Algoritmos , Redes Neurais de Computação , Aprendizado ProfundoRESUMO
A closed-form model of bistatic multiphoton quantum radar cross section (QRCS) for the cylindrical surface, the main structure of typical aircraft, especially missiles, is established to analyze the system and scattering characteristics. The influence of curvature of the three-dimensional target on QRCS is analyzed. By comparing and analyzing the bistatic multiphoton QRCS for a cylinder and a rectangular plate, we find that the QRCS for the convex surface target is the extension of the QRCS for the planar target with inhomogeneous atomic arrangement intervals and patterns. The characteristics of cylindrical QRCS are discussed by combining the transceiver system and the photon number of the transmitted signal, and the influences of the cylindrical radius, cylindrical length, and incident photon number on QRCS are analyzed. The bistatic results provide guidance on potential strong scattering directions for the target under various directions of photon incidence. Compared with the plane target, the cylindrical target amplifies scattering intensity near the target surface at the scattering angle side in the bistatic system. A bistatic multiphoton quantum radar system can achieve sharpening and amplification of the main lobe of the QRCS for a cylinder in an extensive scattering angle range. Bistatic multiphoton quantum radar has better visibility for the cylinder with a smaller length. These characteristics will provide prior information for research in many fields, such as photonic technology, radar technology, and precision metrology.
RESUMO
A closed-form model of multiphoton quantum radar cross-section (QRCS) in the monostatic scenes is constructed for rectangular flat plates based on quantum interference and uncertainty. The model is justified by the comprehensive analysis of the model parameters in the model building process. Then, we use the model to quantitatively analyze the main lobe enhancement effect of multiphoton QRCS, which means that the more incident photons will enhance the main lobe magnitude of QRCS with other factors being the same. Moreover, we predict that enhancement effects might also exist for the side lobe close to the main lobe. In addition, we present the specific conditions for side lobe enhancement. On this basis, the enhancement angle range is defined to unify the description of the main lobe and side lobe enhancement effects. The influencing factors of the enhancement angle range are clarified. The results exhibit that the angle range of enhancement in multiphoton QRCS fluctuates with the change of target size and incident wavelength. All enhancement effects are exponentially related to the incident photon number. This work brings the description of multiphoton QRCS into the closed-form model analysis stage, which will provide prior information for research in many fields, such as photonic technology, radar technology, and precision metrology.
RESUMO
The closed-form expressions of a monostatic quantum radar cross-section (QRCS) for a cuboid under illumination from single photon pulses have been successfully derived. An omnidirectional three-dimensional image of the QRCS is given for the first time using the derived expressions. The simulation results for the expressions are consistent with the numerical calculations, which validate the expressions. The simulation results indicate that the QRCS may have a new slumping effect of different degrees near the special visual angle. The slumping effect means that when the irradiation direction of photon pulses deviates from the vertical direction of the cuboid panel, the QRCS in the main lobe direction drops significantly. We then use the expressions to determine the quantitative relationship between the observed slumping effect and the number of illuminated atoms. In addition, the quantum effect is suppressed (amplified) on the electrically large (small) panel side. This new slumping effect provides good design concepts for quantum stealth aircraft.
RESUMO
Pareuchiloglanis gongshanensis, a small-sized benthic fish, distributed in southwest China. In the present study, the complete mitochondrial genome of P. gongshanensis was sequenced to be 16 588 bp in length, including 13 protein-coding genes, 2 ribosomal RNA genes, 22 transfer RNA genes, a control region and the origin of the light strand replication. The overall nucleotide composition was 30.70% A, 24.11% T, 29.16% C and 16.02% G, with an A + T bias of 54.82%. The gene composition and the structural arrangement of the P. gongshanensis complete mitochondrial DNA were identical to most of the other vertebrates. This will provide a useful tool for understanding the genetic diversity, population structure and conservation status of P. gongshanensis in the future.
