Aiming at the shortcomings of power supply circuit composed of energy storage capacitor and ordinary linear voltage regulator, such as slow power down and input voltage fluctuation affecting output voltage, a power su...
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Autonomous decision-making is crucial for aircraft to achieve quick victories in diverse scenarios. Based on a 6-degree-of-freedom aircraft model, this paper proposes a decoupled guidance and control theory for autono...
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Autonomous decision-making is crucial for aircraft to achieve quick victories in diverse scenarios. Based on a 6-degree-of-freedom aircraft model, this paper proposes a decoupled guidance and control theory for autonomous aircraft maneuvering, distinguishing between close and long-range engagements. We introduce a method for heading attitude control to enhance stability during close-range interactions and a speed-based adaptive grid model for precise waypoint control in mid-to-long-range engagements. The paper transforms dynamic aircraft interactions into a Markov decision process and presents a hybrid discrete and continuous action reinforcement learning approach. This unified learning framework offers enhanced generalization and learning speed for dynamic aircraft adversarial processes. Experimental results indicate that in a symmetric environment, our approach rapidly achieves Nash equilibrium, securing over a 10% advantage. In unmanned aerial aircraft game control with higher maneuverability, the probability of gaining a situational advantage increases by more than 40%. Compared to similar methods, our approach demonstrates superior effectiveness in decision optimization and adversarial success ***, we validate the algorithm's robustness and adaptability in an asymmetric environment, showcasing its promising application potential in collaborative control of aircraft clusters.
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 suf...
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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 *** 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 *** the motion of the UAV platform,the echo signal is sampled at different ***,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 *** 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 *** results of numerical simulations conducted herein verify the superior performance of the proposed method.
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-lea...
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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 ***,dividing the distance between the missile and the target into multiple states to increase the quantity of state ***,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 *** interference effect is determined by detecting whether the fuze signal ***,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 *** 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 *** optimal interference form for each distance state has been *** with the single-interference decision method,the proposed decision method can effectively improve the success rate of interference.
Metal Additive Manufacturing(MAM)technology has become an important means of rapid prototyping precision manufacturing of special high dynamic heterogeneous complex *** response to the micromechanical defects such as ...
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Metal Additive Manufacturing(MAM)technology has become an important means of rapid prototyping precision manufacturing of special high dynamic heterogeneous complex *** response to the micromechanical defects such as porosity issues,significant deformation,surface cracks,and challenging control of surface morphology encountered during the selective laser melting(SLM)additive manufacturing(AM)process of specialized Micro electromechanical System(MEMS)components,multiparameter optimization and micro powder melt pool/macro-scale mechanical properties control simulation of specialized components are *** optimal parameters obtained through highprecision preparation and machining of components and static/high dynamic verification are:laser power of 110 W,laser speed of 600 mm/s,laser diameter of 75 mm,and scanning spacing of 50 *** density of the subordinate components under this reference can reach 99.15%,the surface hardness can reach 51.9 HRA,the yield strength can reach 550 MPa,the maximum machining error of the components is 4.73%,and the average surface roughness is 0.45 *** dynamic hammering and high dynamic firing verification,SLM components meet the requirements for overload *** results have proven that MEM technology can provide a new means for the processing of MEMS components applied in high dynamic *** parameters obtained in the conclusion can provide a design basis for the additive preparation of MEMS components.
The design basis of optical path control of micro optical-electro mechanical fuze safety and arming system is insufficient. Based on working principle of the S&A, the basic theory of laser transmission in optical ...
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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 e...
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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 *** 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 *** 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 *** results show that this method can achieve high-accuracy parameter estimation for LFM signals at an SNR of-25 dB.
Automatic modulation recognition(AMR)of radiation source signals is a research focus in the field of cognitive ***,the AMR of radiation source signals at low SNRs still faces a great ***,the AMR method of radiation so...
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Automatic modulation recognition(AMR)of radiation source signals is a research focus in the field of cognitive ***,the AMR of radiation source signals at low SNRs still faces a great ***,the AMR method of radiation source signals based on two-dimensional data matrix and improved residual neural network is proposed in this ***,the time series of the radiation source signals are reconstructed into two-dimensional data matrix,which greatly simplifies the signal preprocessing ***,the depthwise convolution and large-size convolutional kernels based residual neural network(DLRNet)is proposed to improve the feature extraction capability of the AMR ***,the model performs feature extraction and classification on the two-dimensional data matrix to obtain the recognition vector that represents the signal modulation *** 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 *** recognition accuracy of the proposed method maintains a high level greater than 90% even at -14 dB SNR.
Aiming at the problem of unclear fuse detonation response in the process of different positions of the bullet impact detonator, to carry out research on the dynamic response behaviour of the fuse under the difference ...
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The identification of intercepted radio fuze modulation types is a prerequisite for decision-making in interference ***,the electromagnetic environment of modern battlefields is complex,and the signal-to-noise ratio(S...
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The identification of intercepted radio fuze modulation types is a prerequisite for decision-making in interference ***,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 *** solve the above problem,a radio fuze automatic modulation recognition(AMR)method for low-SNR environments is ***,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)***,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 *** 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 *** 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.
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