This paper proposes a threat assessment framework for non-cooperative satellites by analyzing their motion characteristics,developing a quantitative evaluation methodology,and demonstrating its effectiveness via repre...This paper proposes a threat assessment framework for non-cooperative satellites by analyzing their motion characteristics,developing a quantitative evaluation methodology,and demonstrating its effectiveness via representative scenarios with neural network acceleration.The framework first establishes a threat evaluation model that integrates three core parameters:capability,opportunity,and hidden values.Subsequently,this research systematically investigates the critical role of transfer windows in threat quantification and introduces a transfer window-based threat assessment approach.The proposed methodology is validated through multiple representative scenarios,with simulation results demonstrating superior performance compared to conventional methods relying solely on optimal transfer windows or minimum distance metrics,enabling more nuanced threat ranking in scenarios where traditional techniques prove inadequate.To address computational demands,a neural networkbased approximation system is implemented to achieve a 25,200×speedup(0.005 s vs.baseline 126 s per 1000-sample batch)through parallel processing,maintaining 99.3%accuracy.Finally,the study explores the framework's extensibility to diverse NCS objectives.It identifies discrepancies between intention inference models and threat evaluation paradigms,providing methodological insights for next-generation space domain awareness systems.展开更多
In the field of intelligent air combat,real-time and accurate recognition of within-visual-range(WVR)maneuver actions serves as the foundational cornerstone for constructing autonomous decision-making systems.However,...In the field of intelligent air combat,real-time and accurate recognition of within-visual-range(WVR)maneuver actions serves as the foundational cornerstone for constructing autonomous decision-making systems.However,existing methods face two major challenges:traditional feature engineering suffers from insufficient effective dimensionality in the feature space due to kinematic coupling,making it difficult to distinguish essential differences between maneuvers,while end-to-end deep learning models lack controllability in implicit feature learning and fail to model high-order long-range temporal dependencies.This paper proposes a trajectory feature pre-extraction method based on a Long-range Masked Autoencoder(LMAE),incorporating three key innovations:(1)Random Fragment High-ratio Masking(RFH-Mask),which enforces the model to learn long-range temporal correlations by masking 80%of trajectory data while retaining continuous fragments;(2)Kalman Filter-Guided Objective Function(KFG-OF),integrating trajectory continuity constraints to align the feature space with kinematic principles;and(3)Two-stage Decoupled Architecture,enabling efficient and controllable feature learning through unsupervised pre-training and frozen-feature transfer.Experimental results demonstrate that LMAE significantly improves the average recognition accuracy for 20-class maneuvers compared to traditional end-to-end models,while significantly accelerating convergence speed.The contributions of this work lie in:introducing high-masking-rate autoencoders into low-informationdensity trajectory analysis,proposing a feature engineering framework with enhanced controllability and efficiency,and providing a novel technical pathway for intelligent air combat decision-making systems.展开更多
The pursuit of heat-resistant energetic materials(HREMs)with thermal stability beyond 450℃ presents a significant challenge that has yet to be achieved.In this work,we develop an innovative electronic delocalization ...The pursuit of heat-resistant energetic materials(HREMs)with thermal stability beyond 450℃ presents a significant challenge that has yet to be achieved.In this work,we develop an innovative electronic delocalization strategy to design and synthesize a planar dizwitterionic diamino-bistriazolotetrazine,designated as TYX-1.The unique structural feature of TYX-1,including a nitrogen-rich fused ring system,planar conformation,and dizwitterionic configuration,combined with its hydrogen-bonded organic framework(HOF)structure,confer exceptional thermal stability(The onset temperature is 428℃,and the peak temperature is 473℃),high density(1.84 g/cm^(3)),and remarkable detonation performance(detonation velocity:8616 m/s).Furthermore,TYX-1 exhibits an impressive insensitivity(impact sensitivity>40 J;friction sensitivity>360 N),surpassing all previously reported HREMs.Theoretical calculations and single-crystal clearly indicate that the delocalizedπelectrons within the dizwitterionic bistriazolotetrazine rings and the HOF structure of TYX-1 are pivotal in ensuring its high thermal stability and high energy density.The discovery of TYX-1 marks a significant advancement in the field of HREMs and is anticipated to catalyze substantial progress in various high-temperature applications reliant on energetic materials.展开更多
This work proposes the application of an iterative learning model predictive control(ILMPC)approach based on an adaptive fault observer(FOBILMPC)for fault-tolerant control and trajectory tracking in air-breathing hype...This work proposes the application of an iterative learning model predictive control(ILMPC)approach based on an adaptive fault observer(FOBILMPC)for fault-tolerant control and trajectory tracking in air-breathing hypersonic vehicles.In order to increase the control amount,this online control legislation makes use of model predictive control(MPC)that is based on the concept of iterative learning control(ILC).By using offline data to decrease the linearized model’s faults,the strategy may effectively increase the robustness of the control system and guarantee that disturbances can be suppressed.An adaptive fault observer is created based on the suggested ILMPC approach in order to enhance overall fault tolerance by estimating and compensating for actuator disturbance and fault degree.During the derivation process,a linearized model of longitudinal dynamics is established.The suggested ILMPC approach is likely to be used in the design of hypersonic vehicle control systems since numerical simulations have demonstrated that it can decrease tracking error and speed up convergence when compared to the offline controller.展开更多
Unmanned aerial vehicles(UAVs)have become crucial tools in moving target tracking due to their agility and ability to operate in complex,dynamic environments.UAVs must meet several requirements to achieve stable track...Unmanned aerial vehicles(UAVs)have become crucial tools in moving target tracking due to their agility and ability to operate in complex,dynamic environments.UAVs must meet several requirements to achieve stable tracking,including maintaining continuous target visibility amidst occlusions,ensuring flight safety,and achieving smooth trajectory planning.This paper reviews the latest advancements in UAV-based target tracking,highlighting information prediction,tracking strategies,and swarm cooperation.To address challenges including target visibility and occlusion,real-time prediction and tracking in dynamic environments,flight safety and coordination,resource management and energy efficiency,the paper identifies future research directions aimed at improving the performance,reliability,and scalability of UAV tracking system.展开更多
Recently, high-precision trajectory prediction of ballistic missiles in the boost phase has become a research hotspot. This paper proposes a trajectory prediction algorithm driven by data and knowledge(DKTP) to solve ...Recently, high-precision trajectory prediction of ballistic missiles in the boost phase has become a research hotspot. This paper proposes a trajectory prediction algorithm driven by data and knowledge(DKTP) to solve this problem. Firstly, the complex dynamics characteristics of ballistic missile in the boost phase are analyzed in detail. Secondly, combining the missile dynamics model with the target gravity turning model, a knowledge-driven target three-dimensional turning(T3) model is derived. Then, the BP neural network is used to train the boost phase trajectory database in typical scenarios to obtain a datadriven state parameter mapping(SPM) model. On this basis, an online trajectory prediction framework driven by data and knowledge is established. Based on the SPM model, the three-dimensional turning coefficients of the target are predicted by using the current state of the target, and the state of the target at the next moment is obtained by combining the T3 model. Finally, simulation verification is carried out under various conditions. The simulation results show that the DKTP algorithm combines the advantages of data-driven and knowledge-driven, improves the interpretability of the algorithm, reduces the uncertainty, which can achieve high-precision trajectory prediction of ballistic missile in the boost phase.展开更多
The multi-target assignment(MTA)problem,a crucial challenge in command control,mission planning,and a fundamental research focus in military operations,has garnered significant attention over the years.Extensively stu...The multi-target assignment(MTA)problem,a crucial challenge in command control,mission planning,and a fundamental research focus in military operations,has garnered significant attention over the years.Extensively studied across various domains such as land,sea,air,space,and electronics,the MTA problem has led to the emergence of numerous models and algorithms.To delve deeper into this field,this paper starts by conducting a bibliometric analysis on 463 Scopus database papers using CiteSpace software.The analysis includes examining keyword clustering,co-occurrence,and burst,with visual representations of the results.Following this,the paper provides an overview of current classification and modeling techniques for addressing the MTA problem,distinguishing between static multi-target assignment(SMTA)and dynamic multi-target assignment(DMTA).Subsequently,existing solution algorithms for the MTA problem are reviewed,generally falling into three categories:exact algorithms,heuristic algorithms,and machine learning algorithms.Finally,a development framework is proposed based on the"HIGH"model(high-speed,integrated,great,harmonious)to guide future research and intelligent weapon system development concerning the MTA problem.This framework emphasizes application scenarios,modeling mechanisms,solution algorithms,and system efficiency to offer a roadmap for future exploration in this area.展开更多
The simultaneous integration of high energy density,low sensitivity,and thermal stability in energetic materials has constituted a century-long scientific challenge.Herein,we address this through a dualzwitterionic el...The simultaneous integration of high energy density,low sensitivity,and thermal stability in energetic materials has constituted a century-long scientific challenge.Herein,we address this through a dualzwitterionic electronic delocalization strategy,yielding TYX-3,the first bis-inner salt triazolo-tetrazine framework combining these mutually exclusive properties.Uniformπ-electron distribution and elevated bond dissociation energy confer exceptional thermal stability(T_(d)=365℃)with TATB-level insensitivity(impact sensitivity IS>40 J,friction sensitivity FS>360 N).Engineeredπ-stacked networks enable record density(1.99 g·cm^(-3))with detonation performance surpassing HMX benchmarks(detonation velocity 9315 m·s^(-1),detonation pressure 36.6 GPa).Practical implementation in Poly(3-nitratomethyl-3-methyloxetane)(PNMMFO)solid propellants demonstrates 5.4-fold safety enhancement over conventional HMX-based formulations while maintaining equivalent specific impulse.This work establishes a new design paradigm for energetic materials,overcoming the historical trade-offs between molecular stability and energy output through rational zwitterionic engineering.展开更多
The burgeoning development of nanomedicine has provided state-of-the-art technologies and innovative methodologies for contemporary biomedical research,presenting unprecedented opportunities for resolving pivotal biom...The burgeoning development of nanomedicine has provided state-of-the-art technologies and innovative methodologies for contemporary biomedical research,presenting unprecedented opportunities for resolving pivotal biomedical challenges.Nanomaterials possess distinctive structures and properties.Through the exploration of the fabrication of emerging nanomedicines,multiple functions can be integrated to enable more precise diagnosis and treatment,thereby compensating for the limitations of traditional treatment modalities.Among various substances,polyphenols are natural organic compounds classified as plant secondary metabolites and are ubiquitously present in vegetables,teas,and other plants.Polyphenols are rich in active groups,including hydroxyl,carboxyl,amino,and conjugated double bonds.They exhibit robust adhesion,antioxidant,anti-inflammatory,and antibacterial biological activities and are extensively applied in pharmaceutical formulations.Additionally,polyphenols are characterized by their low cost,ready availability,and do not necessitate intricate chemical synthesis processes.Nevertheless,when natural polyphenol-based nanomedicines are utilized in isolation,they encounter several issues.These include poor water solubility,feeble stability,low bioavailability,the requirement for high dosages,and difficulties in precisely reaching the site of action.To address these concerns,researchers have developed nanomedicines by combining metal ions and functional ligands through metal coordination strategies.Nanomaterials,owing to their unique electronic and optical properties,have been successfully introduced into the realm of medical biology.Nano preparations not only enhance the stability of natural products but also endow them with targeting capabilities,thus enabling precise drug delivery.Polyphenols can further synergize with metal ions,anti-cancer drugs,or photosensitizers via supramolecular interactions to achieve multifunctional synergistic therapies,such as targeted drug delivery,efficacy enhancement,and the construction of engineering scaffolds.Metal-Polyphenol Coordination Polymers(MPCPs),composed of metal ions and phenolic ligands,are regarded as ideal nanoplatforms for disease diagnosis and treatment.In recent years,MPCPs have attracted extensive research in the biomedical field on account of their advantages,including facile synthesis,adjustable structure,excellent biocompatibility,and pH responsiveness.In this review,the classification and preparation strategies of MPCPs were systematically presented.Subsequently,their remarkable achievements in biomedical domains,such as bioimaging,biosensing,drug delivery,tumor therapy,and antimicrobial applications were highlighted.Finally,the principal limitations and prospects of MPCPs were comprehensi vely discussed.展开更多
Taking a C1x motor with a backward-facing step which can generate a typical corner vortex as a reference,a numerical methodology using large eddy simulation was established in this study.Based on this methodology,the ...Taking a C1x motor with a backward-facing step which can generate a typical corner vortex as a reference,a numerical methodology using large eddy simulation was established in this study.Based on this methodology,the position of the backward-facing step of the motor was computed and analyzed to determine a basic configuration.Two key geometrical parameters,the head cavity angle and submerged nozzle cavity height,were subsequently introduced.Their effects on the corner vortex motion and their interactions with the acoustic pressure downstream of the backward-facing step were analyzed.The phenomena of vortex acoustic coupling and characteristics of pressure oscillations were further explored.The results show that the maximum error between the simulations and experimental data on the dominant frequency of pressure oscillations is 5.23%,which indicates that the numerical methodology built in this study is highly accurate.When the step is located at less than 5/8 of the total length of the combustion chamber,vortex acoustic coupling occurs,which can increase the pressure oscillations in the motor.Both the vorticity and the scale of vortices in the downstream step increase when the head cavity angle is greater than 24°,which increases the amplitude of the pressure oscillation by maximum 63.0%.The submerged nozzle cavity mainly affects the vortices in the cavity itself rather than those in the downstream step.When the height of the cavity increases from 10 to 20 mm,the pressure oscillation amplitude under the main frequency increases by 39.1%.As this height continues to increase,the amplitude of pressure oscillations increases but the primary frequency decreases.展开更多
A security issue with multi-sensor unmanned aerial vehicle(UAV)cyber physical systems(CPS)from the viewpoint of a false data injection(FDI)attacker is investigated in this paper.The FDI attacker can employ attacks on ...A security issue with multi-sensor unmanned aerial vehicle(UAV)cyber physical systems(CPS)from the viewpoint of a false data injection(FDI)attacker is investigated in this paper.The FDI attacker can employ attacks on feedback and feed-forward channels simultaneously with limited resource.The attacker aims at degrading the UAV CPS's estimation performance to the max while keeping stealthiness characterized by the Kullback-Leibler(K-L)divergence.The attacker is resource limited which can only attack part of sensors,and the attacked sensor as well as specific forms of attack signals at each instant should be considered by the attacker.Also,the sensor selection principle is investigated with respect to time invariant attack covariances.Additionally,the optimal switching attack strategies in regard to time variant attack covariances are modeled as a multi-agent Markov decision process(MDP)with hybrid discrete-continuous action space.Then,the multi-agent MDP is solved by utilizing the deep Multi-agent parameterized Q-networks(MAPQN)method.Ultimately,a quadrotor near hover system is used to validate the effectiveness of the results in the simulation section.展开更多
The precise characterization of hypersonic glide vehicle(HGV) maneuver laws in complex flight scenarios still faces challenges. Non-stationary changes in flight state due to abrupt changes in maneuver modes place high...The precise characterization of hypersonic glide vehicle(HGV) maneuver laws in complex flight scenarios still faces challenges. Non-stationary changes in flight state due to abrupt changes in maneuver modes place high demands on the accuracy of modeling methods. To address this issue, a novel maneuver laws modeling and analysis method based on higher order multi-resolution dynamic mode decomposition(HMDMD) is proposed in this work. A joint time-space-frequency decomposition of the vehicle's state sequence in the complex flight scenario is achieved with the higher order Koopman assumption and standard multi-resolution dynamic mode decomposition, and an approximate dynamic model is established. The maneuver laws can be reconstructed and analyzed with extracted multi-scale spatiotemporal modes with clear physical meaning. Based on the dynamic model of HGV, two flight scenarios are established with constant angle of attack and complex maneuver laws, respectively. Simulation results demonstrate that the maneuver laws obtained using the HMDMD method are highly consistent with those derived from the real dynamic model, the modeling accuracy is better than other common modeling methods, and the method has strong interpretability.展开更多
Boron-based fuels,recognized for their high energy density and potential in energetic applications,encounter challenges such as long ignition delays and incomplete combustion,which result in reduced combustion efficie...Boron-based fuels,recognized for their high energy density and potential in energetic applications,encounter challenges such as long ignition delays and incomplete combustion,which result in reduced combustion efficiency and limited performance in aerospace propulsion.In this study,boron carbide(B4C)is investigated as an alternative fuel to pristine boron due to its favorable gas-phase combustion.Both metal oxide(nickel oxide(NiO))and metal fluoride(nickel fluoride(NiF_(2)))are selected as oxidizing modifiers to enhance the reactivity of B4C.A method combining laser ignition with optical diagnostics is employed to investigate the enhancing effects of different oxidizers on the ignition and combustion characteristics of B4C.Both NiO and NiF_(2)can significantly increase the combustion radiation intensity and reduce the time to maximum intensity of B4C.Differential scanning calorimetry,in-situ X-ray diffraction,and Fourier transform infrared spectroscopy were used for simultaneous thermal analysis of the B4C composite powders.Combined thermal analysis showed that the effects of NiO and NiF_(2)on promoting B4C combustion is mainly achieved via the formation of NimBn and the release of a large number of gas products.It is reasonable to speculate that the phase separation at the B2O3/NimBn interface forms new pathways for oxygen diffusion and reaction with the B core.The difference in the combustion mechanism of B4C with NiO and NiF_(2)lies in the gas phase products,i.e.,CO_(2)and BF3,respectively,thus leading to significant differences in their reaction processes.展开更多
With its growth in spacecraft control applications,the microcontroller(MCU)becomes increasingly sensitive to radiation and the risks of system failure.In a radiation environment,the MCU is vulnerable to impacts from h...With its growth in spacecraft control applications,the microcontroller(MCU)becomes increasingly sensitive to radiation and the risks of system failure.In a radiation environment,the MCU is vulnerable to impacts from high-energy particles,which can lead to single-event effect(SEE)that disrupt normal system operations.The pipeline of MCU,being the core structure of the system,is particularly susceptible to single-event upset(SEU)and potentially causes execution failures.However,existing radiation-hardening techniques offer limited effectiveness for pipelines.To enhance SEU resistance,this study focused on a 32-bit MCU core with eight pipeline stages,proposing a pipeline hardening approach that utilizes lockstep technology to improve fault tolerance.Signals from two processors were compared including register write data,register contents and pre-fetched instructions.Any discrepancies triggered error flags to indicate faults.When an error flag was raised,recovery was initiated through an interrupt.The interrupt handler then retrieved state information from the advanced peripheral bus(APB)slave module to restore the CPU's operational state and resume execution.By combining hardware-based state preservation with software-driven error recovery,the proposed solution demonstrated significant improvements in fault tolerance rates and performance compared to traditional checkpoint-based techniques.After completing the pipeline hardening design,a fault injection platform was utilized in this paper to simulate real-world error conditions on internal processor modules.The platform was developed based on the circuit's register-transfer-level(RTL)design and statistical results.The fault injection platform was performed by automatically finding all registers within the target design.The register values were forced to upset at the tens of nanoseconds scale in the RTL description of the circuit's design.After running the circuit's functional simulation,the statistics of the faults in registers were displayed on the platform,which evaluated the influence of SEU.The vulnerability of SEU in the circuit could be observed from the results of the soft error statistics.The post-hardening soft error rates were then measured and compared to pre-hardening data,providing a quantitative evaluation of the improvements.Using this method,the soft error rates of the modules in the MCU core such as PFU,DPU,and Cache AXIM are 40.07%,26.36%,and 27.29%respectively before hardening.The soft error rates of modules mentioned above are reduced to 0%,0.69%,and 1.11%after hardening.The hardened and non-hardened designs of the entire core were implemented in FPGA.The total resource utilization of the triple mode redundancy(TMR)is 111984,as indicated by the number of look-up tables(LUTs)and registers consumed in the FPGA.The total resource utilization of this work is 78034,and the ratio of resource utilization between this work and TMR is approximately 69.68%.The error recovery time for the hardened MCU processor was analyzed using the completion cycles of a bubble sort algorithm as a benchmark.In this paper,the average recovery cycle using the software checkpoint roll-back method is 36479.06,and the average recovery cycle using this work is 26922.5.The ratio of recovery cycles between this work and checkpoint roll-back is about 73.8%.Assessments through random fault injection and FPGA implementation indicate that this approach effectively reduces processor faults caused by soft errors while optimizing resource utilization and efficiency over triplemodular redundancy.展开更多
Re-entry gliding vehicles exhibit high maneuverability,making trajectory prediction a key factor in the effectiveness of defense systems.To overcome the limited fitting accuracy of existing methods and their poor adap...Re-entry gliding vehicles exhibit high maneuverability,making trajectory prediction a key factor in the effectiveness of defense systems.To overcome the limited fitting accuracy of existing methods and their poor adaptability to maneuver mode mutations,a trajectory prediction method is proposed that integrates online maneuver mode identification with dynamic modeling.Characteristic parameters are extracted from tracking data for parameterized modeling,enabling real-time identification of maneuver modes.In addition,a maneuver detection mechanism based on higher-order cumulants is introduced to detect lateral maneuver mutations and optimize the use of historical data.Simulation results show that the proposed method achieves accurate trajectory prediction during the glide phase and maintains high accuracy under maneuver mutations,significantly enhancing the prediction performance of both three-dimensional trajectories and ground tracks.展开更多
The objective of the paper is to compute the optimal burn-out conditions and control requirements that would result in maximum down-range/cross-range performance of a waverider type hypersonic boost-glide(HBG) vehicle...The objective of the paper is to compute the optimal burn-out conditions and control requirements that would result in maximum down-range/cross-range performance of a waverider type hypersonic boost-glide(HBG) vehicle within the medium and intermediate ranges,and compare its performance with the performances of wing-body and lifting-body vehicles vis-a-vis the g-load and the integrated heat load experienced by vehicles for the medium-sized launch vehicle under study.Trajectory optimization studies were carried out by considering the heat rate and dynamic pressure constraints.The trajectory optimization problem is modeled as a nonlinear,multiphase,constraint optimal control problem and is solved using a hp-adaptive pseudospectral method.Detail modeling aspects of mass,aerodynamics and aerothermodynamics for the launch and glide vehicles have been discussed.It was found that the optimal burn-out angles for waverider and wing-body configurations are approximately 5° and 14.8°,respectively,for maximum down-range performance under the constraint heat rate environment.The down-range and cross-range performance of HBG waverider configuration is nearly 1.3 and 2 times that of wing-body configuration respectively.The integrated heat load experienced by the HBG waverider was found to be approximately an order of magnitude higher than that of a lifting-body configuration and 5 times that of a wing-body configuration.The footprints and corresponding heat loads and control requirements for the three types of glide vehicles are discussed for the medium range launch vehicle under consideration.展开更多
To diagnose the fault of attitude sensors in satellites, this paper proposes a novel approach based on the Kalman filter of the discrete-time descriptor system. By regarding the sensor fault term as the auxiliary stat...To diagnose the fault of attitude sensors in satellites, this paper proposes a novel approach based on the Kalman filter of the discrete-time descriptor system. By regarding the sensor fault term as the auxiliary state vector, the attitude measurement system subjected to the attitude sensor fault is modeled by the discrete-time descriptor system. The condition of estimability of such systems is given. And then a Kalman filter of the discrete-time descriptor system is established based on the methodology of the maximum likelihood estimation. With the descriptor Kalman filter, the state vector of the original system and sensor fault can be estimated simultaneously. The proposed method is able to esti-mate an abrupt sensor fault as well as the incipient one. Moreover, it is also effective in the multiple faults scenario. Simulations are conducted to confirm the effectiveness of the proposed method.展开更多
A new distributed fusion method of radar/infrared （IR） tracking system based on separation and combination of the measurements is proposed by analyzing the influence of rate measurement. The rate information separat...A new distributed fusion method of radar/infrared （IR） tracking system based on separation and combination of the measurements is proposed by analyzing the influence of rate measurement. The rate information separated from the radar measurements together with measurements of IR form a pseudo vector of IR, and the corresponding filter is designed. The results indicate that the method not only makes a great improvement to the local tracker＇s performance, but also improves the global tracking precision efficiently.展开更多
Aiming at the suppression of enemy air defense(SEAD)task under the complex and complicated combat sce-nario,the spatiotemporal cooperative path planning methods are studied in this paper.The major research contents in...Aiming at the suppression of enemy air defense(SEAD)task under the complex and complicated combat sce-nario,the spatiotemporal cooperative path planning methods are studied in this paper.The major research contents include opti-mal path points generation,path smoothing and cooperative rendezvous.In the path points generation part,the path points availability testing algorithm and the path segments availability testing algorithm are designed,on this foundation,the swarm intelligence-based path point generation algorithm is utilized to generate the optimal path.In the path smoothing part,taking ter-minal attack angle constraint and maneuverability constraint into consideration,the Dubins curve is introduced to smooth the path segments.In cooperative rendezvous part,we take esti-mated time of arrival requirement constraint and flight speed range constraint into consideration,the speed control strategy and flight path control strategy are introduced,further,the decoupling scheme of the circling maneuver and detouring maneuver is designed,in this case,the maneuver ways,maneu-ver point,maneuver times,maneuver path and flight speed are determined.Finally,the simulation experiments are conducted and the acquired results reveal that the time-space cooperation of multiple unmanned aeriel vehicles(UAVs)is effectively real-ized,in this way,the combat situation suppression against the enemy can be realized in SEAD scenarios.展开更多
This paper analyzes the performance of the orthogonal matching pursuit （OMP） algorithm in recovering sparse signals from noisy measurement. Considering the fact that some matrices satisfy some restricted isometry pr...This paper analyzes the performance of the orthogonal matching pursuit （OMP） algorithm in recovering sparse signals from noisy measurement. Considering the fact that some matrices satisfy some restricted isometry properties （RIPs） but not the coherence condition, a superior RIP-based condition is proposed, which means that if the measurement matrix satisfies δk＋1 〈 1/（2 ＋ √k） and the minimum component signal-to-noise ratio （MCSNR） is bounded, the OMP algorithm can exactly identify the support of the original sparse signal within k iterations. Finally, the theoretical results are verified by numerical simulations con- cerning different values of MCSNR and noise levels.展开更多
基金supported by the National Key R&D Programof China:Gravitational Wave Detection Project(Grant Nos.2021YFC2026,2021YFC2202601,2021YFC2202603)the Na-tional Natural Science Foundation of China(Grant Nos.12172288and 12472046)。
文摘This paper proposes a threat assessment framework for non-cooperative satellites by analyzing their motion characteristics,developing a quantitative evaluation methodology,and demonstrating its effectiveness via representative scenarios with neural network acceleration.The framework first establishes a threat evaluation model that integrates three core parameters:capability,opportunity,and hidden values.Subsequently,this research systematically investigates the critical role of transfer windows in threat quantification and introduces a transfer window-based threat assessment approach.The proposed methodology is validated through multiple representative scenarios,with simulation results demonstrating superior performance compared to conventional methods relying solely on optimal transfer windows or minimum distance metrics,enabling more nuanced threat ranking in scenarios where traditional techniques prove inadequate.To address computational demands,a neural networkbased approximation system is implemented to achieve a 25,200×speedup(0.005 s vs.baseline 126 s per 1000-sample batch)through parallel processing,maintaining 99.3%accuracy.Finally,the study explores the framework's extensibility to diverse NCS objectives.It identifies discrepancies between intention inference models and threat evaluation paradigms,providing methodological insights for next-generation space domain awareness systems.
文摘In the field of intelligent air combat,real-time and accurate recognition of within-visual-range(WVR)maneuver actions serves as the foundational cornerstone for constructing autonomous decision-making systems.However,existing methods face two major challenges:traditional feature engineering suffers from insufficient effective dimensionality in the feature space due to kinematic coupling,making it difficult to distinguish essential differences between maneuvers,while end-to-end deep learning models lack controllability in implicit feature learning and fail to model high-order long-range temporal dependencies.This paper proposes a trajectory feature pre-extraction method based on a Long-range Masked Autoencoder(LMAE),incorporating three key innovations:(1)Random Fragment High-ratio Masking(RFH-Mask),which enforces the model to learn long-range temporal correlations by masking 80%of trajectory data while retaining continuous fragments;(2)Kalman Filter-Guided Objective Function(KFG-OF),integrating trajectory continuity constraints to align the feature space with kinematic principles;and(3)Two-stage Decoupled Architecture,enabling efficient and controllable feature learning through unsupervised pre-training and frozen-feature transfer.Experimental results demonstrate that LMAE significantly improves the average recognition accuracy for 20-class maneuvers compared to traditional end-to-end models,while significantly accelerating convergence speed.The contributions of this work lie in:introducing high-masking-rate autoencoders into low-informationdensity trajectory analysis,proposing a feature engineering framework with enhanced controllability and efficiency,and providing a novel technical pathway for intelligent air combat decision-making systems.
基金supported by the National Natural Science Foundation of China(Grant Nos.22105156,22175139,22505195,22171136,22405207 and 22302156)the China National Science Fund for Distinguished Young Scholars(Grant No.22325504)。
文摘The pursuit of heat-resistant energetic materials(HREMs)with thermal stability beyond 450℃ presents a significant challenge that has yet to be achieved.In this work,we develop an innovative electronic delocalization strategy to design and synthesize a planar dizwitterionic diamino-bistriazolotetrazine,designated as TYX-1.The unique structural feature of TYX-1,including a nitrogen-rich fused ring system,planar conformation,and dizwitterionic configuration,combined with its hydrogen-bonded organic framework(HOF)structure,confer exceptional thermal stability(The onset temperature is 428℃,and the peak temperature is 473℃),high density(1.84 g/cm^(3)),and remarkable detonation performance(detonation velocity:8616 m/s).Furthermore,TYX-1 exhibits an impressive insensitivity(impact sensitivity>40 J;friction sensitivity>360 N),surpassing all previously reported HREMs.Theoretical calculations and single-crystal clearly indicate that the delocalizedπelectrons within the dizwitterionic bistriazolotetrazine rings and the HOF structure of TYX-1 are pivotal in ensuring its high thermal stability and high energy density.The discovery of TYX-1 marks a significant advancement in the field of HREMs and is anticipated to catalyze substantial progress in various high-temperature applications reliant on energetic materials.
基金supported by the National Natural Science Foundation of China(12072090).
文摘This work proposes the application of an iterative learning model predictive control(ILMPC)approach based on an adaptive fault observer(FOBILMPC)for fault-tolerant control and trajectory tracking in air-breathing hypersonic vehicles.In order to increase the control amount,this online control legislation makes use of model predictive control(MPC)that is based on the concept of iterative learning control(ILC).By using offline data to decrease the linearized model’s faults,the strategy may effectively increase the robustness of the control system and guarantee that disturbances can be suppressed.An adaptive fault observer is created based on the suggested ILMPC approach in order to enhance overall fault tolerance by estimating and compensating for actuator disturbance and fault degree.During the derivation process,a linearized model of longitudinal dynamics is established.The suggested ILMPC approach is likely to be used in the design of hypersonic vehicle control systems since numerical simulations have demonstrated that it can decrease tracking error and speed up convergence when compared to the offline controller.
基金financial support provided by the Natural Science Foundation of Hunan Province of China(Grant No.2021JJ10045)the Open Research Subject of State Key Laboratory of Intelligent Game(Grant No.ZBKF-24-01)+1 种基金the Postdoctoral Fellowship Program of CPSF(Grant No.GZB20240989)the China Postdoctoral Science Foundation(Grant No.2024M754304)。
文摘Unmanned aerial vehicles(UAVs)have become crucial tools in moving target tracking due to their agility and ability to operate in complex,dynamic environments.UAVs must meet several requirements to achieve stable tracking,including maintaining continuous target visibility amidst occlusions,ensuring flight safety,and achieving smooth trajectory planning.This paper reviews the latest advancements in UAV-based target tracking,highlighting information prediction,tracking strategies,and swarm cooperation.To address challenges including target visibility and occlusion,real-time prediction and tracking in dynamic environments,flight safety and coordination,resource management and energy efficiency,the paper identifies future research directions aimed at improving the performance,reliability,and scalability of UAV tracking system.
基金the National Natural Science Foundation of China (Grants No. 12072090 and No.12302056) to provide fund for conducting experiments。
文摘Recently, high-precision trajectory prediction of ballistic missiles in the boost phase has become a research hotspot. This paper proposes a trajectory prediction algorithm driven by data and knowledge(DKTP) to solve this problem. Firstly, the complex dynamics characteristics of ballistic missile in the boost phase are analyzed in detail. Secondly, combining the missile dynamics model with the target gravity turning model, a knowledge-driven target three-dimensional turning(T3) model is derived. Then, the BP neural network is used to train the boost phase trajectory database in typical scenarios to obtain a datadriven state parameter mapping(SPM) model. On this basis, an online trajectory prediction framework driven by data and knowledge is established. Based on the SPM model, the three-dimensional turning coefficients of the target are predicted by using the current state of the target, and the state of the target at the next moment is obtained by combining the T3 model. Finally, simulation verification is carried out under various conditions. The simulation results show that the DKTP algorithm combines the advantages of data-driven and knowledge-driven, improves the interpretability of the algorithm, reduces the uncertainty, which can achieve high-precision trajectory prediction of ballistic missile in the boost phase.
基金the financial support provided by the National Natural Science Foundation of China(NSFC)(Grant No.62173274)the National Key R&D Program of China(Grant No.2019YFA0405300)+4 种基金the Natural Science Foundation of Hunan Province of China(Grant No.2021JJ10045)the Practice and Innovation Funds for Graduate Students of Northwestern Polytechnical University(Grant No.PF2023046)the Open Research Subject of State Key Laboratory of Intelligent Game(Grant No.ZBKF-24-01)the Postdoctoral Fellowship Program of CPSF(No.GZB20240989)the China Postdoctoral Science Foundation(Grant No.2024M754304)。
文摘The multi-target assignment(MTA)problem,a crucial challenge in command control,mission planning,and a fundamental research focus in military operations,has garnered significant attention over the years.Extensively studied across various domains such as land,sea,air,space,and electronics,the MTA problem has led to the emergence of numerous models and algorithms.To delve deeper into this field,this paper starts by conducting a bibliometric analysis on 463 Scopus database papers using CiteSpace software.The analysis includes examining keyword clustering,co-occurrence,and burst,with visual representations of the results.Following this,the paper provides an overview of current classification and modeling techniques for addressing the MTA problem,distinguishing between static multi-target assignment(SMTA)and dynamic multi-target assignment(DMTA).Subsequently,existing solution algorithms for the MTA problem are reviewed,generally falling into three categories:exact algorithms,heuristic algorithms,and machine learning algorithms.Finally,a development framework is proposed based on the"HIGH"model(high-speed,integrated,great,harmonious)to guide future research and intelligent weapon system development concerning the MTA problem.This framework emphasizes application scenarios,modeling mechanisms,solution algorithms,and system efficiency to offer a roadmap for future exploration in this area.
基金supported by the National Natural Science Foundation of China(Grant Nos.22105156,22175139,22171136,and 22302156)the China National Science Fund for Distinguished Young Scholars(Grant No.22325504)。
文摘The simultaneous integration of high energy density,low sensitivity,and thermal stability in energetic materials has constituted a century-long scientific challenge.Herein,we address this through a dualzwitterionic electronic delocalization strategy,yielding TYX-3,the first bis-inner salt triazolo-tetrazine framework combining these mutually exclusive properties.Uniformπ-electron distribution and elevated bond dissociation energy confer exceptional thermal stability(T_(d)=365℃)with TATB-level insensitivity(impact sensitivity IS>40 J,friction sensitivity FS>360 N).Engineeredπ-stacked networks enable record density(1.99 g·cm^(-3))with detonation performance surpassing HMX benchmarks(detonation velocity 9315 m·s^(-1),detonation pressure 36.6 GPa).Practical implementation in Poly(3-nitratomethyl-3-methyloxetane)(PNMMFO)solid propellants demonstrates 5.4-fold safety enhancement over conventional HMX-based formulations while maintaining equivalent specific impulse.This work establishes a new design paradigm for energetic materials,overcoming the historical trade-offs between molecular stability and energy output through rational zwitterionic engineering.
文摘The burgeoning development of nanomedicine has provided state-of-the-art technologies and innovative methodologies for contemporary biomedical research,presenting unprecedented opportunities for resolving pivotal biomedical challenges.Nanomaterials possess distinctive structures and properties.Through the exploration of the fabrication of emerging nanomedicines,multiple functions can be integrated to enable more precise diagnosis and treatment,thereby compensating for the limitations of traditional treatment modalities.Among various substances,polyphenols are natural organic compounds classified as plant secondary metabolites and are ubiquitously present in vegetables,teas,and other plants.Polyphenols are rich in active groups,including hydroxyl,carboxyl,amino,and conjugated double bonds.They exhibit robust adhesion,antioxidant,anti-inflammatory,and antibacterial biological activities and are extensively applied in pharmaceutical formulations.Additionally,polyphenols are characterized by their low cost,ready availability,and do not necessitate intricate chemical synthesis processes.Nevertheless,when natural polyphenol-based nanomedicines are utilized in isolation,they encounter several issues.These include poor water solubility,feeble stability,low bioavailability,the requirement for high dosages,and difficulties in precisely reaching the site of action.To address these concerns,researchers have developed nanomedicines by combining metal ions and functional ligands through metal coordination strategies.Nanomaterials,owing to their unique electronic and optical properties,have been successfully introduced into the realm of medical biology.Nano preparations not only enhance the stability of natural products but also endow them with targeting capabilities,thus enabling precise drug delivery.Polyphenols can further synergize with metal ions,anti-cancer drugs,or photosensitizers via supramolecular interactions to achieve multifunctional synergistic therapies,such as targeted drug delivery,efficacy enhancement,and the construction of engineering scaffolds.Metal-Polyphenol Coordination Polymers(MPCPs),composed of metal ions and phenolic ligands,are regarded as ideal nanoplatforms for disease diagnosis and treatment.In recent years,MPCPs have attracted extensive research in the biomedical field on account of their advantages,including facile synthesis,adjustable structure,excellent biocompatibility,and pH responsiveness.In this review,the classification and preparation strategies of MPCPs were systematically presented.Subsequently,their remarkable achievements in biomedical domains,such as bioimaging,biosensing,drug delivery,tumor therapy,and antimicrobial applications were highlighted.Finally,the principal limitations and prospects of MPCPs were comprehensi vely discussed.
基金Sponsored by the Natural Science Foundation of Shaanxi Province (Grant No. S2025-JC-YB-0532)the Practice and Innovation Funds for Graduate Students of Northwestern Polytechnical University (PF2024044)
文摘Taking a C1x motor with a backward-facing step which can generate a typical corner vortex as a reference,a numerical methodology using large eddy simulation was established in this study.Based on this methodology,the position of the backward-facing step of the motor was computed and analyzed to determine a basic configuration.Two key geometrical parameters,the head cavity angle and submerged nozzle cavity height,were subsequently introduced.Their effects on the corner vortex motion and their interactions with the acoustic pressure downstream of the backward-facing step were analyzed.The phenomena of vortex acoustic coupling and characteristics of pressure oscillations were further explored.The results show that the maximum error between the simulations and experimental data on the dominant frequency of pressure oscillations is 5.23%,which indicates that the numerical methodology built in this study is highly accurate.When the step is located at less than 5/8 of the total length of the combustion chamber,vortex acoustic coupling occurs,which can increase the pressure oscillations in the motor.Both the vorticity and the scale of vortices in the downstream step increase when the head cavity angle is greater than 24°,which increases the amplitude of the pressure oscillation by maximum 63.0%.The submerged nozzle cavity mainly affects the vortices in the cavity itself rather than those in the downstream step.When the height of the cavity increases from 10 to 20 mm,the pressure oscillation amplitude under the main frequency increases by 39.1%.As this height continues to increase,the amplitude of pressure oscillations increases but the primary frequency decreases.
文摘A security issue with multi-sensor unmanned aerial vehicle(UAV)cyber physical systems(CPS)from the viewpoint of a false data injection(FDI)attacker is investigated in this paper.The FDI attacker can employ attacks on feedback and feed-forward channels simultaneously with limited resource.The attacker aims at degrading the UAV CPS's estimation performance to the max while keeping stealthiness characterized by the Kullback-Leibler(K-L)divergence.The attacker is resource limited which can only attack part of sensors,and the attacked sensor as well as specific forms of attack signals at each instant should be considered by the attacker.Also,the sensor selection principle is investigated with respect to time invariant attack covariances.Additionally,the optimal switching attack strategies in regard to time variant attack covariances are modeled as a multi-agent Markov decision process(MDP)with hybrid discrete-continuous action space.Then,the multi-agent MDP is solved by utilizing the deep Multi-agent parameterized Q-networks(MAPQN)method.Ultimately,a quadrotor near hover system is used to validate the effectiveness of the results in the simulation section.
基金supported by the National Natural Science Foundation of China (Grant No. 12302056)the Postdoctoral Fellowship Program of CPSF:GZC20233445。
文摘The precise characterization of hypersonic glide vehicle(HGV) maneuver laws in complex flight scenarios still faces challenges. Non-stationary changes in flight state due to abrupt changes in maneuver modes place high demands on the accuracy of modeling methods. To address this issue, a novel maneuver laws modeling and analysis method based on higher order multi-resolution dynamic mode decomposition(HMDMD) is proposed in this work. A joint time-space-frequency decomposition of the vehicle's state sequence in the complex flight scenario is achieved with the higher order Koopman assumption and standard multi-resolution dynamic mode decomposition, and an approximate dynamic model is established. The maneuver laws can be reconstructed and analyzed with extracted multi-scale spatiotemporal modes with clear physical meaning. Based on the dynamic model of HGV, two flight scenarios are established with constant angle of attack and complex maneuver laws, respectively. Simulation results demonstrate that the maneuver laws obtained using the HMDMD method are highly consistent with those derived from the real dynamic model, the modeling accuracy is better than other common modeling methods, and the method has strong interpretability.
基金The National Natural Science Foundation of China(Grant Nos.523B2063 and 52376089)。
文摘Boron-based fuels,recognized for their high energy density and potential in energetic applications,encounter challenges such as long ignition delays and incomplete combustion,which result in reduced combustion efficiency and limited performance in aerospace propulsion.In this study,boron carbide(B4C)is investigated as an alternative fuel to pristine boron due to its favorable gas-phase combustion.Both metal oxide(nickel oxide(NiO))and metal fluoride(nickel fluoride(NiF_(2)))are selected as oxidizing modifiers to enhance the reactivity of B4C.A method combining laser ignition with optical diagnostics is employed to investigate the enhancing effects of different oxidizers on the ignition and combustion characteristics of B4C.Both NiO and NiF_(2)can significantly increase the combustion radiation intensity and reduce the time to maximum intensity of B4C.Differential scanning calorimetry,in-situ X-ray diffraction,and Fourier transform infrared spectroscopy were used for simultaneous thermal analysis of the B4C composite powders.Combined thermal analysis showed that the effects of NiO and NiF_(2)on promoting B4C combustion is mainly achieved via the formation of NimBn and the release of a large number of gas products.It is reasonable to speculate that the phase separation at the B2O3/NimBn interface forms new pathways for oxygen diffusion and reaction with the B core.The difference in the combustion mechanism of B4C with NiO and NiF_(2)lies in the gas phase products,i.e.,CO_(2)and BF3,respectively,thus leading to significant differences in their reaction processes.
文摘With its growth in spacecraft control applications,the microcontroller(MCU)becomes increasingly sensitive to radiation and the risks of system failure.In a radiation environment,the MCU is vulnerable to impacts from high-energy particles,which can lead to single-event effect(SEE)that disrupt normal system operations.The pipeline of MCU,being the core structure of the system,is particularly susceptible to single-event upset(SEU)and potentially causes execution failures.However,existing radiation-hardening techniques offer limited effectiveness for pipelines.To enhance SEU resistance,this study focused on a 32-bit MCU core with eight pipeline stages,proposing a pipeline hardening approach that utilizes lockstep technology to improve fault tolerance.Signals from two processors were compared including register write data,register contents and pre-fetched instructions.Any discrepancies triggered error flags to indicate faults.When an error flag was raised,recovery was initiated through an interrupt.The interrupt handler then retrieved state information from the advanced peripheral bus(APB)slave module to restore the CPU's operational state and resume execution.By combining hardware-based state preservation with software-driven error recovery,the proposed solution demonstrated significant improvements in fault tolerance rates and performance compared to traditional checkpoint-based techniques.After completing the pipeline hardening design,a fault injection platform was utilized in this paper to simulate real-world error conditions on internal processor modules.The platform was developed based on the circuit's register-transfer-level(RTL)design and statistical results.The fault injection platform was performed by automatically finding all registers within the target design.The register values were forced to upset at the tens of nanoseconds scale in the RTL description of the circuit's design.After running the circuit's functional simulation,the statistics of the faults in registers were displayed on the platform,which evaluated the influence of SEU.The vulnerability of SEU in the circuit could be observed from the results of the soft error statistics.The post-hardening soft error rates were then measured and compared to pre-hardening data,providing a quantitative evaluation of the improvements.Using this method,the soft error rates of the modules in the MCU core such as PFU,DPU,and Cache AXIM are 40.07%,26.36%,and 27.29%respectively before hardening.The soft error rates of modules mentioned above are reduced to 0%,0.69%,and 1.11%after hardening.The hardened and non-hardened designs of the entire core were implemented in FPGA.The total resource utilization of the triple mode redundancy(TMR)is 111984,as indicated by the number of look-up tables(LUTs)and registers consumed in the FPGA.The total resource utilization of this work is 78034,and the ratio of resource utilization between this work and TMR is approximately 69.68%.The error recovery time for the hardened MCU processor was analyzed using the completion cycles of a bubble sort algorithm as a benchmark.In this paper,the average recovery cycle using the software checkpoint roll-back method is 36479.06,and the average recovery cycle using this work is 26922.5.The ratio of recovery cycles between this work and checkpoint roll-back is about 73.8%.Assessments through random fault injection and FPGA implementation indicate that this approach effectively reduces processor faults caused by soft errors while optimizing resource utilization and efficiency over triplemodular redundancy.
基金supported by the National Natural Science Foundation of China(12302056)the Postdoctoral Fellowship Program of China Postdoctoral Science Foundation(GZC20233445)。
文摘Re-entry gliding vehicles exhibit high maneuverability,making trajectory prediction a key factor in the effectiveness of defense systems.To overcome the limited fitting accuracy of existing methods and their poor adaptability to maneuver mode mutations,a trajectory prediction method is proposed that integrates online maneuver mode identification with dynamic modeling.Characteristic parameters are extracted from tracking data for parameterized modeling,enabling real-time identification of maneuver modes.In addition,a maneuver detection mechanism based on higher-order cumulants is introduced to detect lateral maneuver mutations and optimize the use of historical data.Simulation results show that the proposed method achieves accurate trajectory prediction during the glide phase and maintains high accuracy under maneuver mutations,significantly enhancing the prediction performance of both three-dimensional trajectories and ground tracks.
基金the Chinese Scholarship Council for supporting the research
文摘The objective of the paper is to compute the optimal burn-out conditions and control requirements that would result in maximum down-range/cross-range performance of a waverider type hypersonic boost-glide(HBG) vehicle within the medium and intermediate ranges,and compare its performance with the performances of wing-body and lifting-body vehicles vis-a-vis the g-load and the integrated heat load experienced by vehicles for the medium-sized launch vehicle under study.Trajectory optimization studies were carried out by considering the heat rate and dynamic pressure constraints.The trajectory optimization problem is modeled as a nonlinear,multiphase,constraint optimal control problem and is solved using a hp-adaptive pseudospectral method.Detail modeling aspects of mass,aerodynamics and aerothermodynamics for the launch and glide vehicles have been discussed.It was found that the optimal burn-out angles for waverider and wing-body configurations are approximately 5° and 14.8°,respectively,for maximum down-range performance under the constraint heat rate environment.The down-range and cross-range performance of HBG waverider configuration is nearly 1.3 and 2 times that of wing-body configuration respectively.The integrated heat load experienced by the HBG waverider was found to be approximately an order of magnitude higher than that of a lifting-body configuration and 5 times that of a wing-body configuration.The footprints and corresponding heat loads and control requirements for the three types of glide vehicles are discussed for the medium range launch vehicle under consideration.
基金supported by the National Natural Science Foundation of China (60874054)
文摘To diagnose the fault of attitude sensors in satellites, this paper proposes a novel approach based on the Kalman filter of the discrete-time descriptor system. By regarding the sensor fault term as the auxiliary state vector, the attitude measurement system subjected to the attitude sensor fault is modeled by the discrete-time descriptor system. The condition of estimability of such systems is given. And then a Kalman filter of the discrete-time descriptor system is established based on the methodology of the maximum likelihood estimation. With the descriptor Kalman filter, the state vector of the original system and sensor fault can be estimated simultaneously. The proposed method is able to esti-mate an abrupt sensor fault as well as the incipient one. Moreover, it is also effective in the multiple faults scenario. Simulations are conducted to confirm the effectiveness of the proposed method.
基金supported by the National Natural Science Foundation of China (60574022).
文摘A new distributed fusion method of radar/infrared （IR） tracking system based on separation and combination of the measurements is proposed by analyzing the influence of rate measurement. The rate information separated from the radar measurements together with measurements of IR form a pseudo vector of IR, and the corresponding filter is designed. The results indicate that the method not only makes a great improvement to the local tracker＇s performance, but also improves the global tracking precision efficiently.
文摘Aiming at the suppression of enemy air defense(SEAD)task under the complex and complicated combat sce-nario,the spatiotemporal cooperative path planning methods are studied in this paper.The major research contents include opti-mal path points generation,path smoothing and cooperative rendezvous.In the path points generation part,the path points availability testing algorithm and the path segments availability testing algorithm are designed,on this foundation,the swarm intelligence-based path point generation algorithm is utilized to generate the optimal path.In the path smoothing part,taking ter-minal attack angle constraint and maneuverability constraint into consideration,the Dubins curve is introduced to smooth the path segments.In cooperative rendezvous part,we take esti-mated time of arrival requirement constraint and flight speed range constraint into consideration,the speed control strategy and flight path control strategy are introduced,further,the decoupling scheme of the circling maneuver and detouring maneuver is designed,in this case,the maneuver ways,maneu-ver point,maneuver times,maneuver path and flight speed are determined.Finally,the simulation experiments are conducted and the acquired results reveal that the time-space cooperation of multiple unmanned aeriel vehicles(UAVs)is effectively real-ized,in this way,the combat situation suppression against the enemy can be realized in SEAD scenarios.
基金supported by the National Natural Science Foundation of China(6117401661171197)
文摘This paper analyzes the performance of the orthogonal matching pursuit （OMP） algorithm in recovering sparse signals from noisy measurement. Considering the fact that some matrices satisfy some restricted isometry properties （RIPs） but not the coherence condition, a superior RIP-based condition is proposed, which means that if the measurement matrix satisfies δk＋1 〈 1/（2 ＋ √k） and the minimum component signal-to-noise ratio （MCSNR） is bounded, the OMP algorithm can exactly identify the support of the original sparse signal within k iterations. Finally, the theoretical results are verified by numerical simulations con- cerning different values of MCSNR and noise levels.
