Metal–organic gel(MOG)derived composites are promising multi-functional materials due to their alterable composition,identifiable chemical homogeneity,tunable shape,and porous structure.Herein,stable metal–organic h...Metal–organic gel(MOG)derived composites are promising multi-functional materials due to their alterable composition,identifiable chemical homogeneity,tunable shape,and porous structure.Herein,stable metal–organic hydrogels are prepared by regulating the complexation effect,solution polarity and curing speed.Meanwhile,collagen peptide is used to facilitate the fabrication of a porous aerogel with excellent physical properties as well as the homogeneous dispersion of magnetic particles during calcination.Subsequently,two kinds of heterometallic magnetic coupling systems are obtained through the application of Kirkendall effect.FeCo/nitrogen-doped carbon(NC)aerogel demonstrates an ultra-strong microwave absorption of−85 dB at an ultra-low loading of 5%.After reducing the time taken by atom shifting,a FeCo/Fe3O4/NC aerogel containing virus-shaped particles is obtained,which achieves an ultra-broad absorption of 7.44 GHz at an ultra-thin thickness of 1.59 mm due to the coupling effect offered by dual-soft-magnetic particles.Furthermore,both aerogels show excellent thermal insulation property,and their outstanding radar stealth performances in J-20 aircraft are confirmed by computer simulation technology.The formation mechanism of MOG is also discussed along with the thermal insulation and electromagnetic wave absorption mechanism of the aerogels,which will enable the development and application of novel and lightweight stealth coatings.展开更多
Millimeter-wave(mmWave)radar communication has emerged as an important technique for future wireless systems.However,the interference between the radar signal and communication data is the main issue that should be co...Millimeter-wave(mmWave)radar communication has emerged as an important technique for future wireless systems.However,the interference between the radar signal and communication data is the main issue that should be considered for the joint radar communication system.In this paper,a co-sharing waveform(CSW)is proposed to achieve communication and radar sensing simultaneously.To eliminate the co-interference between the communication and sensing signal,signal splitting and processing methods for communication data demodulation and radar signal processing are given respectively.Simulation results show that the bit error rate(BER)of CSW is close to that of the pure communication waveform.Moreover,the proposed CSW can achieve better performance than the existing waveforms in terms of range and velocity estimation.展开更多
The task of modeling and analyzing intercepted multifunction radars(MFRs)pulse trains is vital for cognitive electronic reconnaissance.Existing methodologies predominantly rely on prior information or heavily constrai...The task of modeling and analyzing intercepted multifunction radars(MFRs)pulse trains is vital for cognitive electronic reconnaissance.Existing methodologies predominantly rely on prior information or heavily constrained models,posing challenges for non-cooperative applications.This paper introduces a novel approach to model MFRs using a Bayesian network,where the conditional probability density function is approximated by an autoregressive kernel mixture network(ARKMN).Utilizing the estimated probability density function,a dynamic programming algorithm is proposed for denoising and detecting change points in the intercepted MFRs pulse trains.Simulation results affirm the proposed method's efficacy in modeling MFRs,outperforming the state-of-the-art in pulse train denoising and change point detection.展开更多
Cognitive radar is a concept proposed by Simon Haykin in 2006 as a new generation of radar system that imitates human cognitive features.Different from the adaptive signal processing at the receiver in adaptive radar,...Cognitive radar is a concept proposed by Simon Haykin in 2006 as a new generation of radar system that imitates human cognitive features.Different from the adaptive signal processing at the receiver in adaptive radar,the cognitive radar realizes closedloop adaptive policy adjustment of both transmitter and receiver in the continuous interaction with the environment.As a networked radar may significantly enhance the flexibility and robustness than its monostatic counterpart,the wireless networked cognitive radar(WNCR)attracts increasing research.This article firstly reviews the concept and development of cognitive radar,especially the related researches of networked cognitive radar.Then,the co-design of cognitive radar and communication is investigated.Although the communication quality between radar sensing nodes is the premise of detection,tracking,imaging and anti-jamming performance of the WNCR,the latest researches seldom consider the communication architecture design for WNCR.Therefore,this article mainly focuses on the proposal of WNCR concept based on the researches of cognitive radar and analyzes research challenges of WNCR system in practical application,and the corresponding guidelines are proposed to inspire future research.展开更多
Reduction of the radar cross-section(RCS) is the key to stealth technology. To improve the RCS reduction effect of the designed checkerboard metasurface and overcome the limitation of thinlayer plasma in RCS reduction...Reduction of the radar cross-section(RCS) is the key to stealth technology. To improve the RCS reduction effect of the designed checkerboard metasurface and overcome the limitation of thinlayer plasma in RCS reduction technology, a double-layer-plasma-based metasurface—composed of a checkerboard metasurface, a double-layer plasma and an air gap between them—was investigated. Based on the principle of backscattering cancellation, we designed a checkerboard metasurface composed of different artificial magnetic conductor units;the checkerboard metasurface can reflect vertically incident electromagnetic(EM) waves in four different inclined directions to reduce the RCS. Full-wave simulations confirm that the doublelayer-plasma-based metasurface can improve the RCS reduction effect of the metasurface and the plasma. This is because in a band lower than the working band of the metasurface, the RCS reduction effect is mainly improved by the plasma layer. In the working band of the metasurface,impedance mismatching between the air gap and first plasma layer and between first and second plasma layers cause the scattered waves to become more dispersed, so the propagation path of the EM waves in the plasma becomes longer, increasing the absorption of the EM waves by the plasma. Thus, the RCS reduction effect is enhanced. The double-layer-plasma-based metasurface can be insensitive to the polarization of the incoming EM waves, and can also maintain a satisfactory RCS reduction band when the incident waves are oblique.展开更多
This study presents an innovative approach to improving the performance of YOLO-v8 model for small object detection in radar images.Initially,a local histogram equalization technique was applied to the original images...This study presents an innovative approach to improving the performance of YOLO-v8 model for small object detection in radar images.Initially,a local histogram equalization technique was applied to the original images,resulting in a notable enhancement in both contrast and detail representation.Subsequently,the YOLO-v8 backbone network was augmented by incorporating convolutional kernels based on a multidimensional attention mechanism and a parallel processing strategy,which facilitated more effective feature information fusion.At the model’s head,an upsampling layer was added,along with the fusion of outputs from the shallow network,and a detection head specifically tailored for small object detection,thereby further improving accuracy.Additionally,the loss function was modified to incorporate focal-intersection over union(IoU)in conjunction with scaled-IoU,which enhanced the model’s performance.A weighting strategy was also introduced,effectively improving detection accuracy for small targets.Experimental results demonstrate that the customized model outperforms traditional approaches across various evaluation metrics,including recall,precision,F1-score,and the receiver operating characteristic(ROC)curve,validating its efficacy and innovation in small object detection within radar imagery.The results indicate a substantial improvement in accuracy compared to conventional methods such as image segmentation and standard convolutional neural networks.展开更多
Long-time integration technique is an effective way of improving target detection performance for unmanned aerial vehicle(UAV)in the passive bistatic radar(PBR),while range migration(RM)and Doppler frequency migration...Long-time integration technique is an effective way of improving target detection performance for unmanned aerial vehicle(UAV)in the passive bistatic radar(PBR),while range migration(RM)and Doppler frequency migration(DFM)may have a major effect due to the target maneuverability.This paper proposed an innovative long-time coherent integration approach,regarded as Continuous Radon-matched filtering process(CRMFP),for low-observable UAV target in passive bistatic radar.It not only mitigates the RM by collaborative research in range and velocity dimensions but also compensates the DFM and ensures the coherent integration through the matched filtering process(MFP).Numerical and real-life data following detailed analysis verify that the proposed method can overcome the Doppler mismatch influence and acquire comparable detection performance.展开更多
Channel equalization plays a pivotal role within the reconstruction phase of passive radar reference signals.In the context of reconstructing digital terrestrial multimedia broadcasting(DTMB)signals for low-slow-small...Channel equalization plays a pivotal role within the reconstruction phase of passive radar reference signals.In the context of reconstructing digital terrestrial multimedia broadcasting(DTMB)signals for low-slow-small(LSS)target detection,a novel frequency domain block joint equalization algorithm is presented in this article.From the DTMB signal frame structure and channel multipath transmission characteristics,this article adopts a unconventional approach where the delay and frame structure of each DTMB signal frame are reconfigured to create a circular convolution block,facilitating concurrent fast Fourier transform(FFT)calculations.Following equalization,an inverse fast Fourier transform(IFFT)-based joint output and subsequent data reordering are executed to finalize the equalization process for the DTMB signal.Simulation and measured data confirm that this algorithm outperforms conventional techniques by reducing signal errors rate and enhancing real-time processing.In passive radar LSS detection,it effectively suppresses multipath and noise through frequency domain equalization,reducing false alarms and improving the capabilities of weak target detection.展开更多
Gesture recognition plays an increasingly important role as the requirements of intelligent systems for human-computer interaction methods increase.To improve the accuracy of the millimeter-wave radar gesture detectio...Gesture recognition plays an increasingly important role as the requirements of intelligent systems for human-computer interaction methods increase.To improve the accuracy of the millimeter-wave radar gesture detection algorithm with limited computational resources,this study improves the detection performance in terms of optimized features and interference filtering.The accuracy of the algorithm is improved by refining the combination of gesture features using a self-constructed dataset,and biometric filtering is introduced to reduce the interference of inanimate object motion.Finally,experiments demonstrate the effectiveness of the proposed algorithm in both mitigating interference from inanimate objects and accurately recognizing gestures.Results show a notable 93.29%average reduction in false detections achieved through the integration of biometric filtering into the algorithm’s interpretation of target movements.Additionally,the algorithm adeptly identifies the six gestures with an average accuracy of 96.84%on embedded systems.展开更多
基金the National Natural Science Foundation of China(22265021)the Aeronautical Science Foundation of China(2020Z056056003).
文摘Metal–organic gel(MOG)derived composites are promising multi-functional materials due to their alterable composition,identifiable chemical homogeneity,tunable shape,and porous structure.Herein,stable metal–organic hydrogels are prepared by regulating the complexation effect,solution polarity and curing speed.Meanwhile,collagen peptide is used to facilitate the fabrication of a porous aerogel with excellent physical properties as well as the homogeneous dispersion of magnetic particles during calcination.Subsequently,two kinds of heterometallic magnetic coupling systems are obtained through the application of Kirkendall effect.FeCo/nitrogen-doped carbon(NC)aerogel demonstrates an ultra-strong microwave absorption of−85 dB at an ultra-low loading of 5%.After reducing the time taken by atom shifting,a FeCo/Fe3O4/NC aerogel containing virus-shaped particles is obtained,which achieves an ultra-broad absorption of 7.44 GHz at an ultra-thin thickness of 1.59 mm due to the coupling effect offered by dual-soft-magnetic particles.Furthermore,both aerogels show excellent thermal insulation property,and their outstanding radar stealth performances in J-20 aircraft are confirmed by computer simulation technology.The formation mechanism of MOG is also discussed along with the thermal insulation and electromagnetic wave absorption mechanism of the aerogels,which will enable the development and application of novel and lightweight stealth coatings.
基金supported by the National Natural Science Foundation of China(No.62171052 and No.61971054)the Fundamental Research Funds for the Central Universities(No.24820232023YQTD01).
文摘Millimeter-wave(mmWave)radar communication has emerged as an important technique for future wireless systems.However,the interference between the radar signal and communication data is the main issue that should be considered for the joint radar communication system.In this paper,a co-sharing waveform(CSW)is proposed to achieve communication and radar sensing simultaneously.To eliminate the co-interference between the communication and sensing signal,signal splitting and processing methods for communication data demodulation and radar signal processing are given respectively.Simulation results show that the bit error rate(BER)of CSW is close to that of the pure communication waveform.Moreover,the proposed CSW can achieve better performance than the existing waveforms in terms of range and velocity estimation.
基金supported by the National Natural Science Foundation of China under Grant 62301119。
文摘The task of modeling and analyzing intercepted multifunction radars(MFRs)pulse trains is vital for cognitive electronic reconnaissance.Existing methodologies predominantly rely on prior information or heavily constrained models,posing challenges for non-cooperative applications.This paper introduces a novel approach to model MFRs using a Bayesian network,where the conditional probability density function is approximated by an autoregressive kernel mixture network(ARKMN).Utilizing the estimated probability density function,a dynamic programming algorithm is proposed for denoising and detecting change points in the intercepted MFRs pulse trains.Simulation results affirm the proposed method's efficacy in modeling MFRs,outperforming the state-of-the-art in pulse train denoising and change point detection.
基金This work was supported by the National Natural Science Foundation of China under Grant No.91948303.
文摘Cognitive radar is a concept proposed by Simon Haykin in 2006 as a new generation of radar system that imitates human cognitive features.Different from the adaptive signal processing at the receiver in adaptive radar,the cognitive radar realizes closedloop adaptive policy adjustment of both transmitter and receiver in the continuous interaction with the environment.As a networked radar may significantly enhance the flexibility and robustness than its monostatic counterpart,the wireless networked cognitive radar(WNCR)attracts increasing research.This article firstly reviews the concept and development of cognitive radar,especially the related researches of networked cognitive radar.Then,the co-design of cognitive radar and communication is investigated.Although the communication quality between radar sensing nodes is the premise of detection,tracking,imaging and anti-jamming performance of the WNCR,the latest researches seldom consider the communication architecture design for WNCR.Therefore,this article mainly focuses on the proposal of WNCR concept based on the researches of cognitive radar and analyzes research challenges of WNCR system in practical application,and the corresponding guidelines are proposed to inspire future research.
基金supported in part by the China Postdoctoral Science Foundation (No. 2020M673341)in part by the Natural Science Basic Research Program of Shaanxi (No.2023-JC-YB-549)+1 种基金in part by National Natural Science Foundation of China (Nos. 62371375 and 62371372)Innovation Capability Support Program of Shaanxi (No. 2022TD-37)。
文摘Reduction of the radar cross-section(RCS) is the key to stealth technology. To improve the RCS reduction effect of the designed checkerboard metasurface and overcome the limitation of thinlayer plasma in RCS reduction technology, a double-layer-plasma-based metasurface—composed of a checkerboard metasurface, a double-layer plasma and an air gap between them—was investigated. Based on the principle of backscattering cancellation, we designed a checkerboard metasurface composed of different artificial magnetic conductor units;the checkerboard metasurface can reflect vertically incident electromagnetic(EM) waves in four different inclined directions to reduce the RCS. Full-wave simulations confirm that the doublelayer-plasma-based metasurface can improve the RCS reduction effect of the metasurface and the plasma. This is because in a band lower than the working band of the metasurface, the RCS reduction effect is mainly improved by the plasma layer. In the working band of the metasurface,impedance mismatching between the air gap and first plasma layer and between first and second plasma layers cause the scattered waves to become more dispersed, so the propagation path of the EM waves in the plasma becomes longer, increasing the absorption of the EM waves by the plasma. Thus, the RCS reduction effect is enhanced. The double-layer-plasma-based metasurface can be insensitive to the polarization of the incoming EM waves, and can also maintain a satisfactory RCS reduction band when the incident waves are oblique.
基金supported by the Na‑tional Natural Science Foundation of China Joint Fund(No.U21B2028)the National Key R&D Program of China(No.2021YFC 2100100)the Shanghai Science and Technology Project(Nos.21JC1403400,23JC1402300).
文摘This study presents an innovative approach to improving the performance of YOLO-v8 model for small object detection in radar images.Initially,a local histogram equalization technique was applied to the original images,resulting in a notable enhancement in both contrast and detail representation.Subsequently,the YOLO-v8 backbone network was augmented by incorporating convolutional kernels based on a multidimensional attention mechanism and a parallel processing strategy,which facilitated more effective feature information fusion.At the model’s head,an upsampling layer was added,along with the fusion of outputs from the shallow network,and a detection head specifically tailored for small object detection,thereby further improving accuracy.Additionally,the loss function was modified to incorporate focal-intersection over union(IoU)in conjunction with scaled-IoU,which enhanced the model’s performance.A weighting strategy was also introduced,effectively improving detection accuracy for small targets.Experimental results demonstrate that the customized model outperforms traditional approaches across various evaluation metrics,including recall,precision,F1-score,and the receiver operating characteristic(ROC)curve,validating its efficacy and innovation in small object detection within radar imagery.The results indicate a substantial improvement in accuracy compared to conventional methods such as image segmentation and standard convolutional neural networks.
基金supported by the National Natural Science Foundation of China (Nos.51975447,52275268)National Key Research and Development Program of China (No.2021YFC2203600)+2 种基金National Defense Basic Scientific Research Program of China (No.JCKY2021210B007)the Project about Building up“Scientists+Engineers”of Shaanxi Qinchuangyuan Platform (No.2022KXJ-030)Wuhu and Xidian University Special Fund for Industry University Research Cooperation (No.XWYCXY012021-012)。
文摘Long-time integration technique is an effective way of improving target detection performance for unmanned aerial vehicle(UAV)in the passive bistatic radar(PBR),while range migration(RM)and Doppler frequency migration(DFM)may have a major effect due to the target maneuverability.This paper proposed an innovative long-time coherent integration approach,regarded as Continuous Radon-matched filtering process(CRMFP),for low-observable UAV target in passive bistatic radar.It not only mitigates the RM by collaborative research in range and velocity dimensions but also compensates the DFM and ensures the coherent integration through the matched filtering process(MFP).Numerical and real-life data following detailed analysis verify that the proposed method can overcome the Doppler mismatch influence and acquire comparable detection performance.
文摘Channel equalization plays a pivotal role within the reconstruction phase of passive radar reference signals.In the context of reconstructing digital terrestrial multimedia broadcasting(DTMB)signals for low-slow-small(LSS)target detection,a novel frequency domain block joint equalization algorithm is presented in this article.From the DTMB signal frame structure and channel multipath transmission characteristics,this article adopts a unconventional approach where the delay and frame structure of each DTMB signal frame are reconfigured to create a circular convolution block,facilitating concurrent fast Fourier transform(FFT)calculations.Following equalization,an inverse fast Fourier transform(IFFT)-based joint output and subsequent data reordering are executed to finalize the equalization process for the DTMB signal.Simulation and measured data confirm that this algorithm outperforms conventional techniques by reducing signal errors rate and enhancing real-time processing.In passive radar LSS detection,it effectively suppresses multipath and noise through frequency domain equalization,reducing false alarms and improving the capabilities of weak target detection.
基金supported by the National Natural Science Foundation of China(No.12172076)。
文摘Gesture recognition plays an increasingly important role as the requirements of intelligent systems for human-computer interaction methods increase.To improve the accuracy of the millimeter-wave radar gesture detection algorithm with limited computational resources,this study improves the detection performance in terms of optimized features and interference filtering.The accuracy of the algorithm is improved by refining the combination of gesture features using a self-constructed dataset,and biometric filtering is introduced to reduce the interference of inanimate object motion.Finally,experiments demonstrate the effectiveness of the proposed algorithm in both mitigating interference from inanimate objects and accurately recognizing gestures.Results show a notable 93.29%average reduction in false detections achieved through the integration of biometric filtering into the algorithm’s interpretation of target movements.Additionally,the algorithm adeptly identifies the six gestures with an average accuracy of 96.84%on embedded systems.
