Automatic modulation recognition of radiation source signals based on two-dimensional data matrix and improved residual neural network

Automatic modulation recognition(AMR)of radiation source signals is a research focus in the field of cognitive radio.However,the AMR of radiation source signals at low SNRs still faces a great challenge.Therefore,the AMR method of radiation source signals based on two-dimensional data matrix and improved residual neural network is proposed in this paper.First,the time series of the radiation source signals are reconstructed into two-dimensional data matrix,which greatly simplifies the signal preprocessing process.Second,the depthwise convolution and large-size convolutional kernels based residual neural network(DLRNet)is proposed to improve the feature extraction capability of the AMR model.Finally,the model performs feature extraction and classification on the two-dimensional data matrix to obtain the recognition vector that represents the signal modulation type.Theoretical analysis and simulation results show that the AMR method based on two-dimensional data matrix and improved residual network can significantly improve the accuracy of the AMR method.The recognition accuracy of the proposed method maintains a high level greater than 90% even at -14 dB SNR.

Underdetermined direction of arrival estimation with nonuniform linear motion sampling based on a small unmanned aerial vehicle platform

Uniform linear array(ULA)radars are widely used in the collision-avoidance radar systems of small unmanned aerial vehicles(UAVs).In practice,a ULA's multi-target direction of arrival(DOA)estimation performance suffers from significant performance degradation owing to the limited number of physical elements.To improve the underdetermined DOA estimation performance of a ULA radar mounted on a small UAV platform,we propose a nonuniform linear motion sampling underdetermined DOA estimation method.Using the motion of the UAV platform,the echo signal is sampled at different positions.Then,according to the concept of difference co-array,a virtual ULA with multiple array elements and a large aperture is synthesized to increase the degrees of freedom(DOFs).Through position analysis of the original and motion arrays,we propose a nonuniform linear motion sampling method based on ULA for determining the optimal DOFs.Under the condition of no increase in the aperture of the physical array,the proposed method obtains a high DOF with fewer sampling runs and greatly improves the underdetermined DOA estimation performance of ULA.The results of numerical simulations conducted herein verify the superior performance of the proposed method.

Cognitive interference decision method for air defense missile fuze based on reinforcement learning

To solve the problem of the low interference success rate of air defense missile radio fuzes due to the unified interference form of the traditional fuze interference system,an interference decision method based Q-learning algorithm is proposed.First,dividing the distance between the missile and the target into multiple states to increase the quantity of state spaces.Second,a multidimensional motion space is utilized,and the search range of which changes with the distance of the projectile,to select parameters and minimize the amount of ineffective interference parameters.The interference effect is determined by detecting whether the fuze signal disappears.Finally,a weighted reward function is used to determine the reward value based on the range state,output power,and parameter quantity information of the interference form.The effectiveness of the proposed method in selecting the range of motion space parameters and designing the discrimination degree of the reward function has been verified through offline experiments involving full-range missile rendezvous.The optimal interference form for each distance state has been obtained.Compared with the single-interference decision method,the proposed decision method can effectively improve the success rate of interference.

Automatic modulation recognition of radio fuzes using a DR2D-based adaptive denoising method and textural feature extraction

The identification of intercepted radio fuze modulation types is a prerequisite for decision-making in interference systems.However,the electromagnetic environment of modern battlefields is complex,and the signal-to-noise ratio(SNR)of such environments is usually low,which makes it difficult to implement accurate recognition of radio fuzes.To solve the above problem,a radio fuze automatic modulation recognition(AMR)method for low-SNR environments is proposed.First,an adaptive denoising algorithm based on data rearrangement and the two-dimensional(2D)fast Fourier transform(FFT)(DR2D)is used to reduce the noise of the intercepted radio fuze intermediate frequency(IF)signal.Then,the textural features of the denoised IF signal rearranged data matrix are extracted from the statistical indicator vectors of gray-level cooccurrence matrices(GLCMs),and support vector machines(SVMs)are used for classification.The DR2D-based adaptive denoising algorithm achieves an average correlation coefficient of more than 0.76 for ten fuze types under SNRs of-10 d B and above,which is higher than that of other typical algorithms.The trained SVM classification model achieves an average recognition accuracy of more than 96%on seven modulation types and recognition accuracies of more than 94%on each modulation type under SNRs of-12 d B and above,which represents a good AMR performance of radio fuzes under low SNRs.

Parameter estimation method for a linear frequency modulation signal with a Duffing oscillator based on frequency periodicity

In view of the complexity of existing linear frequency modulation(LFM)signal parameter estimation methods and the poor antinoise performance and estimation accuracy under a low signal-to-noise ratio(SNR),a parameter estimation method for LFM signals with a Duffing oscillator based on frequency periodicity is proposed in this paper.This method utilizes the characteristic that the output signal of the Duffing oscillator excited by the LFM signal changes periodically with frequency,and the modulation period of the LFM signal is estimated by autocorrelation processing of the output signal of the Duffing oscillator.On this basis,the corresponding relationship between the reference frequency of the frequencyaligned Duffing oscillator and the frequency range of the LFM signal is analyzed by the periodic power spectrum method,and the frequency information of the LFM signal is determined.Simulation results show that this method can achieve high-accuracy parameter estimation for LFM signals at an SNR of-25 dB.

Synchronously scrambled diffuse image encryption method based on a new cosine chaotic map

We present a new cosine chaotic mapping proved by chaos theory test and analysis such that the system has good cryptography properties, wide chaos range, simple structure, and good sensitivity to initial value, and the mapping can meet the needs of chaotic image encryption. Based on the cosine chaotic system, we propose a new encryption method. First,according to the cyclic characteristics of the mapping, the cyclic information wave is simulated. Second, the quasi-Doppler effect is used to synchronously scramble and diffuse the image to obfuscate the original pixel. Finally, the XOR diffusion of image pixels is carried out by information wave to further enhance the encryption effect. Simulation experiment and security analysis show that the algorithm has good security, can resist the common attack mode, and has good efficiency.

A Local Reference Frame Construction Method Based on the Signed Surface Variation

A fast local reference frame(LRF)construction method based on the signed surface variation is proposed,which can adapt to the real-time applications such as self-driving,face recognition,object detection.The z-axis of the LRF is generated based on the concavity of the local surface of keypoint.The x-axis is constructed by the weighted vector sum of a set of projection vectors of the local neighborhoods around keypoint.The performance of the proposed LRF is evaluated on six standard datasets and compared with six state-of-the-art LRF construction methods(e.g.,BOARD,FLARE,SHOT,RoPS and TOLDI).Experimental results validate the high repeatability,robustness,universality and time efficiency of our method.

磁压榨吻合技术治疗结直肠吻合及重建中的应用分析

回顾磁压榨吻合技术(magnetic compression anastomosis,MCA)治疗不同原因、不同类型肠道狭窄/闭锁实现肠道再通的案例,对MCA在结直肠吻合及重建中的临床应用进行分析探讨。4例患者2019年5月—2022年8月在西安交通大学第一附属医院及西北妇女儿童医院行结直肠MCA再通治疗。患者手术过程均顺利,实现肠道吻合再通,磁环排出时间为7~15 d,术后复查肠镜或造影提示吻合口完好。MCA可用于治疗不同原因、不同类型的结直肠狭窄及闭锁,也可用于辅助结直肠手术肠吻合。

磁外科学体系的探索与建立

21世纪外科学领域利用磁性装置进行技术创新和革新的报道越来越多,其中某些技术显示出极大的优越性和颠覆性,有取代传统技术的趋势.主要体现在两个方面:一方面,部分先进的磁外科创新技术可极大地简化现有手术操作过程、降低操作难度、缩短操作时间、提高治疗效果;另一方面借助先进的磁外科技术,对一些临床疾病的治疗模式和观念产生了颠覆性的改变.然而,就目前世界各地的相关研究现状来看,存在着很多关键共性瓶颈问题,比如:基础研究薄弱,核心关键问题未能系统突破,理工科先进技术交叉、渗透、融合不充分,科学概念及临床应用规范未建立等.我国医学界虽然涉足磁外科技术开发领域较晚,但却在磁外科方面进行了相对系统化的研究,产生了一系列国际首创技术,尤其是在理论创新和学科化建设方面走在了世界前列,承担起了世界磁外科领跑者的角色.本文以创建国际磁外科体系为主线,评述磁外科发展现状和基础;对磁外科发展阶段进行科学划分;明确提出了磁外科临床应用五大体系并建立相应的概念;提出通过跨学科交叉整合的方法来创建磁外科学体系.以求夯实磁外科基础研究、建立磁外科理论体系、规范磁外科临床研究、强化磁性材料、生物力学和临床诊疗技术深度交叉融合,凝聚稀土金属材料专家、生物力学专家和临床医生的智慧,全面建立磁外科学理论体系并开展临床应用研究,从而促进磁外科快速科学发展,造福人类健康.

Construction of an intrahepatic portosystemic shunt using the magnetic compression technique: preliminary experiments in a canine model

Portal hypertension caused by liver cirrhosis due to hepatitis is a common clinical condition that can cause bleeding from esophageal and gastric varices in severe cases.In 1969,Rösch et al.first described a successful transjugular intrahepatic portosystemic shunt(TIPS)in animal experiments(1).In 1989,Richter et al.first used this technology in clinical practice(2).

Restrictive versus liberal fluid therapy for major abdominal surgery: is the evidence strong?

We have read with great interest the original study by Myles et al. (1), in which the authors claimed a restrictive fluid regimen during and up to 24 hours after major abdominal surgery was associated with higher rate of acute kidney injury. This international, randomized, assessor-blinded trail compared the following outcomes between restrictive and liberal intravenous-fluid regimen: disability-free survival at 1 year, acute kidney injury at 30 days, renal-replacement therapy at 90 days, septic complications, surgical-site infection, and death. The perioperative fluid management is of great clinical significance, the results demonstrated by Myles et al. provide high-level evidence with dedicate design and adequate case volume, serving as potential reference to guidelines of surgical patient care. Shortly after its online publication, the article has drawn tremendous attention and caused extensive discussion among surgeons world-wide.

Experimental study on the controlling factors of frictional coefficient for lost circulation control and formation damage prevention in deep fractured tight reservoir

Working fluids loss is a major contributor to low productivity during production process of fractured tight reservoirs.Lost circulation control effect directly related to the tribological behavior between fracture surface and lost circulation materials(LCMs).In this study,the friction coefficient(FC)was investigated using typical clastic rocks and LCMs by considering multiple effect factors divided into external condition and internal condition.The results show that normal load had a relatively high effect on sliding model.A positive correlation was observed between FC and asperities heights.FC decreased induced by particle size degradation of rigid LCMs.Elastic LCMs manifested higher FC compared with rigid LCMs.Under the lubrication condition by working fluid,FC of rigid LCMs was mainly controlled by their surface wettability.FC of organic LCMs is more sensitive to high temperature aging than inorganic LCMs.Fracture plugging experiments show that LCMs optimized based on the research results can effectively improve the efficiency and strength of fracture plugging.