Enhancing Dense Small Object Detection in UAV Images Based on Hybrid Transformer

Transformer-based models have facilitated significant advances in object detection.However,their extensive computational consumption and suboptimal detection of dense small objects curtail their applicability in unmanned aerial vehicle(UAV)imagery.Addressing these limitations,we propose a hybrid transformer-based detector,H-DETR,and enhance it for dense small objects,leading to an accurate and efficient model.Firstly,we introduce a hybrid transformer encoder,which integrates a convolutional neural network-based cross-scale fusion module with the original encoder to handle multi-scale feature sequences more efficiently.Furthermore,we propose two novel strategies to enhance detection performance without incurring additional inference computation.Query filter is designed to cope with the dense clustering inherent in drone-captured images by counteracting similar queries with a training-aware non-maximum suppression.Adversarial denoising learning is a novel enhancement method inspired by adversarial learning,which improves the detection of numerous small targets by counteracting the effects of artificial spatial and semantic noise.Extensive experiments on the VisDrone and UAVDT datasets substantiate the effectiveness of our approach,achieving a significant improvement in accuracy with a reduction in computational complexity.Our method achieves 31.9%and 21.1%AP on the VisDrone and UAVDT datasets,respectively,and has a faster inference speed,making it a competitive model in UAV image object detection.

Equipment damage measurement method of wartime based on FCE-PCA-RF

As the“engine”of equipment continuous operation and repeated operation, equipment maintenance support plays a more prominent role in the confrontation of symmetrical combat systems. As the basis and guide for the planning and implementation of equipment maintenance tasks, the equipment damage measurement is an important guarantee for the effective implementation of maintenance support. Firstly,this article comprehensively analyses the influence factors to damage measurement from the enemy’s attributes, our attributes and the battlefield environment starting from the basic problem of wartime equipment damage measurement. Secondly, this article determines the key factors based on fuzzy comprehensive evaluation(FCE) and performed principal component analysis (PCA) on the key factors. Finally, the principal components representing more than 85%of the data features are taken as the input and the equipment damage quantity is taken as the output. The data are trained and tested by artificial neural network (ANN) and random forest (RF). In a word, FCE-PCA-RF can be used as a reference for the research of equipment damage estimation in wartime.

An extended state observer with adjustable bandwidth for measurement noise

In this paper,a bandwidth-adjustable extended state observer(ABESO)is proposed for the systems with measurement noise.It is known that increasing the bandwidth of the observer improves the tracking speed but tolerates noise,which conflicts with observation accuracy.Therefore,we introduce a bandwidth scaling factor such that ABESO is formulated to a 2-degree-of-freedom system.The observer gain is determined and the bandwidth scaling factor adjusts the bandwidth according to the tracking error.When the tracking error decreases,the bandwidth decreases to suppress the noise,otherwise the bandwidth does not change.It is proven that the error dynamics are bounded and converge in finite time.The relationship between the upper bound of the estimation error and the scaling factor is given.When the scaling factor is less than 1,the ABESO has higher estimation accuracy than the linear extended state observer(LESO).Simulations of an uncertain nonlinear system with compound disturbances show that the proposed ABESO can successfully estimate the total disturbance in noisy environments.The mean error of total disturbance of ABESO is 15.28% lower than that of LESO.

Mechanical behavior and response mechanism of porous metal structures manufactured by laser powder bed fusion under compressive loading

Al Si10Mg porous protective structure often produces different damage forms under compressive loading,and these damage modes affect its protective function.In order to well meet the service requirements,there is an urgent need to comprehensively understand the mechanical behavior and response mechanism of AlSi10Mg porous structures under compressive loading.In this paper,Al Si10Mg porous structures with three kinds of volume fractions are designed and optimized to meet the requirements of high-impact,strong-energy absorption,and lightweight characteristics.The mechanical behaviors of AlSi10Mg porous structures,including the stress-strain relationship,structural bearing state,deformation and damage modes,and energy absorption characteristics,were obtained through experimental studies at different loading rates.The damage pattern of the damage section indicates that AlSi10Mg porous structures have both ductile and brittle mechanical properties.Numerical simulation studies show that the AlSi10Mg porous structure undergoes shear damage due to relative misalignment along the diagonal cross-section,and the damage location is almost at 45°to the load direction,which is the most direct cause of its structural damage,revealing the damage mechanism of AlSi10Mg porous structures under the compressive load.The normalized energy absorption model constructed in the paper well interprets the energy absorption state of Al Si10Mg porous structures and gives the sensitive location of the structures,and the results of this paper provide important references for peers in structural design and optimization.

Research on Infrared Emissivity and Laser Reflectivity of Sn_(1−x)Er_(x)O_(2)Micro/Nanofibers Based on First-Principles

Sn_(1−x)Er_(x)O_(2)(x=0%,8%,16%,24%)micro/nanofibers were prepared by electrospinning combined with heat treatment using erbium nitrate,stannous chloride and polyvinylpyrrolidone(PVP)as raw materials.The target products were characterized by thermogravimetric analyzer,X-ray diffrotometer,fourier transform infrared spectrometer,scanning electron microscope,spectrophotometer and infrared emissivity tester,and the effects of Er^(3+)doping on its infrared and laser emissivity were studied.At the same time,the Sn_(1−x)Er_(x)O_(2)(x=0%,16%)doping models were constructed based on the first principles of density functional theory,and the related optoelectronic properties such as their energy band structure,density of states,reflectivity and dielectric constant were analyzed,and further explained the mechanism of Er^(3+)doping on SnO_(2)infrared emissivity and laser absorption from the point of electronic structure.The results showed that after calcination at 600℃,single rutile type SnO_(2)was formed,and the crystal structure was not changed by doping Er^(3+).The calcined products showed good fiber morphology,and the average fiber diameter was 402 nm.The infrared emissivity and resistivity of the samples both decreased first and then increased with the increase of Er^(3+)doping amount.When x=16%,the infrared emis-sivity of the sample was at least 0.71;and Er^(3+)doping can effectively reduce the reflectivity of SnO_(2)at 1.06μm and 1.55μm,when x=16%,its reflectivity at 1.06μm and 1.55μm are 50.5%and 40%,respectively,when x=24%,the reflectivity at 1.06μm and 1.55μm wavelengths are 47.3%and 42.1%,respectively.At the same time,the change of carrier concentration and electron transition before and after Er^(3+)doping were described by first-principle calculation,and the regulation mechanism of infrared emissivity and laser reflectivity was explained.This study provides a certain experimental and theoretical basis for the development of a single-type,light-weight and easily prepared infrared and laser compatible-stealth material.

Optimization of extended warranty cost for multi-component systems with economic dependence based on group maintenance

During extended warranty(EW)period,maintenance events play a key role in controlling the product systems within normal operations.However,the modelling of failure process and maintenance optimization is complicated owing to the complex features of the product system,namely,components of the multi-component system are interdependent with each other in some form.For the purpose of optimizing the EW pricing decision of the multi-component system scientifically and rationally,taking the series multi-component system with economic dependence sold with EW policy as a research object,this paper optimizes the imperfect preventive maintenance(PM)strategy from the standpoint of EW cost.Taking into consideration adjusting the PM moments of the components in the system,a group maintenance model is developed,in which the system is repaired preventively in accordance with a specified PM base interval.In order to compare with the system EW cost before group maintenance,the system EW cost model before group maintenance is developed.Numerical example demonstrates that offering group maintenance programs can reduce EW cost of the system to a great extent,thereby reducing the EW price,which proves to be a win-win strategy to manufacturers and users.

Analysis and Compensation of Frequency Offset in Co-Site Adjacent Channel Interference Suppression

Due to the mismatch of the circuit oscillators,there will always be a frequency offset between the transmitter and the receiver.In the adjacent channel interference(ACI)suppression system using the reconstruction and cancellation method,the frequency offset decreases the accuracy of the reconstructed signal and introduces a time-varying term in the interference cancellation,resulting in poor performance of the ACI suppression.In this paper,the relationship between the normalized frequency offset,signal-to-noise ratio and the loss of interference suppression capability is analyzed through formula derivation and simulation.The validity of the frequency offset compensation method based on the pilot sequence is verified,and the relationship between the sequence length and the estimation accuracy is given.This paper provides necessary method reference and data support for the engineering of ACI suppression.

Automatic recognition of tweek atmospherics and plasma diagnostics in the lower ionosphere with the machine learning method

Tweek atmospherics are extremely low frequency and very low frequency pulse signals with frequency dispersion characteristics that originate from lightning discharges and that propagate in the Earth–ionosphere waveguide over long distances.In this study,we developed an automatic method to recognize tweek atmospherics and diagnose the lower ionosphere based on the machine learning method.The differences(automatic−manual)in each ionosphere parameter between the automatic method and the manual method were−0.07±2.73 km,0.03±0.92 cm^(−3),and 91±1,068 km for the ionospheric reflection height(h),equivalent electron densities at reflection heights(Ne),and propagation distance(d),respectively.Moreover,the automatic method is capable of recognizing higher harmonic tweek sferics.The evaluation results of the model suggest that the automatic method is a powerful tool for investigating the long-term variations in the lower ionosphere.

Dynamic Prediction Method for Valuable Spare Parts Demand in Weaponry Equipment Based on Data Perception

Missile is an important weapon system of the army.The spare parts of missile equipment are significant effect on military operations.In order to improve the mission completion rate of missile equipment in wartime,this paper introduces data sensing method to forecast the demand of valuable spare parts of missile equipment dynamically.Firstly,the information related to valuable spare parts of missile equipment was obtained by data sensing,and the sample size was determined by Bernoulli uniform sampling probability.Secondly,according to the data quality of multi-source and multi-modal,the data requirement for dynamic demand prediction of valuable spare parts of missile equipment was obtained.Finally,according to the characteristics of the spare parts,the life of the spare parts was predicted,realizing the dynamic prediction of the demand for valuable spare parts of missile equipment.The results show that the demand of valuable spare parts of missile equipment can be predicted dynamically by using this method,the accuracy is higher than 95%,and the real-time performance is more excellent.

Sensor scheduling for ground maneuvering target tracking in presence of detection blind zone

Continuous and stable tracking of the ground maneuvering target is a challenging problem due to the complex terrain and high clutter. A collaborative tracking method of the multisensor network is presented for the ground maneuvering target in the presence of the detection blind zone(DBZ). First, the sensor scheduling process is modeled within the partially observable Markov decision process(POMDP) framework. To evaluate the target tracking accuracy of the sensor, the Fisher information is applied to constructing the reward function. The key of the proposed scheduling method is forecasting and early decisionmaking. Thus, an approximate method based on unscented sampling is presented to estimate the target state and the multi-step scheduling reward over the prediction time horizon. Moreover, the problem is converted into a nonlinear optimization problem, and a fast search algorithm is given to solve the sensor scheduling scheme quickly. Simulation results demonstrate the proposed nonmyopic scheduling method(Non-MSM) has a better target tracking accuracy compared with traditional methods.

Sensor radiation interception risk control in target tracking

This paper is mainly on the problem of radiation interception risk control in sensor network for target tracking.Firstly,the sensor radiation interception risk is defined as the product of the interception probability and the cost caused by the interception.Secondly,the radiation interception probability model and cost model are established,based on which the calculation method of interception risk can be obtained.Thirdly,a sensor scheduling model of radiation risk control is established,taking the minimum interception risk as the objective function.Then the Hungarian algorithm is proposed to obtain sensor scheduling scheme.Finally,simulation experiments are mad to prove the effectiveness of the methods proposed in this paper,which shows that compared with the sensor radiation interception probability control method,the interception risk control method can keep the sensor scheduling scheme in low risk as well as protect sensors of importance in the sensor network.

Arbitrary-oriented target detection in large scene sar images

Target detection in the field of synthetic aperture radar(SAR) has attracted considerable attention of researchers in national defense technology worldwide,owing to its unique advantages like high resolution and large scene image acquisition capabilities of SAR.However,due to strong speckle noise and low signal-to-noise ratio,it is difficult to extract representative features of target from SAR images,which greatly inhibits the effectiveness of traditional methods.In order to address the above problems,a framework called contextual rotation region-based convolutional neural network(RCNN) with multilayer fusion is proposed in this paper.Specifically,aimed to enable RCNN to perform target detection in large scene SAR images efficiently,maximum sliding strategy is applied to crop the large scene image into a series of sub-images before RCNN.Instead of using the highest-layer output for proposal generation and target detection,fusion feature maps with high resolution and rich semantic information are constructed by multilayer fusion strategy.Then,we put forwards rotation anchors to predict the minimum circumscribed rectangle of targets to reduce redundant detection region.Furthermore,shadow areas serve as contextual features to provide extraneous information for the detector identify and locate targets accurately.Experimental results on the simulated large scene SAR image dataset show that the proposed method achieves a satisfactory performance in large scene SAR target detection.

Storage life prediction under pre-strained thermally-accelerated aging of HTPB coating using the change of crosslinking density

In order to predict the storage life of a certain type of HTPB(hydroyl-terminated polybutadiene)coating at 25℃ and analyze the influence of pre-strain on the storage life,the accelerated aging tests of HTPB coating at 40℃,50℃,60℃,70℃ with the pre-strain of 0%,3%,6%,9%,respectively were carried out.The variation regularity of the change of crosslinking density was analyzed and the aging model of HTPB coating under pre-strained thermally-accelerated aging was proposed.The storage life of HTPB coating at 25℃ was estimated by using the Berthelot equation as the end point of the aging life with a 30% decrease in maximum elongation.The results showed that the change of crosslinking density of HTPB coating increased with the increase of aging temperature and aging time,and decreased with the increase of pre-strain.Under 0% prestrain,the relationship between the change of crosslinking density of HTPB coating and the aging time can be described by the logarithmic model with the confidence probability greater than 99%.The stress relaxation phenomenon existed under 3%,6%and 9%pre-strained aging.The aging model considering chemical aging and pre-strain was established with the confidence probability greater than 90%.The storage life of HTPB coating was 15.2935 years at 25C under 0% prestrain,which was reduced by 13.9007%,75.6949% and 89.7859% under 3%,6% and 9% pre-strain,respectively.The existence of pre-strain has a serious impact on the storage life of HTPB coating,therefore,the pre-strain should be avoided as much as possible during the actual storage.

Multi-objectives nonlinear structure optimization for actuator in trajectory correction fuze subject to high impact loadings

This paper presents an actuator used for the trajectory correction fuze,which is subject to high impact loadings during launch.A simulation method is carried out to obtain the peak-peak stress value of each component,from which the ball bearings are possible failures according to the results.Subsequently,three schemes against impact loadings,full-element deep groove ball bearing and integrated raceway,needle roller thrust bearing assembly,and gaskets are utilized for redesigning the actuator to effectively reduce the bearings’stress.However,multi-objectives optimization still needs to be conducted for the gaskets to decrease the stress value further to the yield stress.Four gasket’s structure parameters and three bearings’peak-peak stress are served as the four optimization variables and three objectives,respectively.Optimized Latin hypercube design is used for generating sample points,and Kriging model selected according to estimation result can establish the relationship between the variables and objectives,representing the simulation which is time-consuming.Accordingly,two optimization algorithms work out the Pareto solutions,from which the best solutions are selected,and verified by the simulation to determine the gaskets optimized structure parameters.It can be concluded that the simulation and optimization method based on these components is effective and efficient.

Priori information analysis of optocoupler accelerated degradation experiment based on failure mechanism verification test

The optocoupler is a weak link in the inertial navigation platform of a kind of guided munitions.It is necessary to use accelerated storage test to verify the storage life of long storage products.Especially for small sample products,it is very important to obtain prior information for the design and implementation of accelerated degradation test.In this paper,the optocoupler failure mechanism verification test is designed and the experimental results are analyzed and the prior information is obtained.The results show that optocouplers have two failure modes,one is sudden failure and the other is degradation failure;the maximum temperature stress of optocoupler can’t exceed 140℃;the increase of leakage current of optocoupler is caused by movable ions contaminating the LED chip.The surface leakage current is proportional to the adsorption amount.The increase of leakage current makes p-n junction tunneling effect occur which LEDs the failure of the optocoupler.The lifetime distribution model of the optocoupler is determined by the failure physics.The lifetime of the optocoupler is subject to the lognormal distribution.The degeneracy orbit of the optocoupler leakage current is described by a power law model.The estimated values of the orbital parameters are initially calculated and the parameters of its life distribution function are deduced.The above information lays a good foundation for the optimization design and data processing of the accelerated degradation experiment.

Transverse relaxation characteristic and stress relaxation model considering molecular chains of HTPB coating based on pre-strained thermal aging

In order to accurately describe the transverse relaxation characteristic and stress relaxation modulus of HTPB coating during pre-strain thermal aging process,a one month thermal aging test was carried out at70C with pre-strain of 0%,3%,6%and 9%,respectively.The low-field1 H NMR and stress relaxation modulus tests were carried out for HTPB coating at different aging stages.The stress relaxation model considering the molecular chains was proposed according to the changes of crosslinking chain and dangling chain of HTPB coating during pre-strain aging.The results showed that with the increase of aging time,the decay rate of transverse relaxation curve became faster,the transverse relaxation time decreased,the value of combined parameter q Mrl increased,the proportion of crosslinking chain decreased,while the proportion of dangling chain increased.Moreover,the stress relaxation modulus increased,the crosslinking network structure of HTPB coating became denser and the degree of crosslinking increased.At the initial aging stage,the pre-strain will destroy the crosslinking network structure of HTPB coating to a certain extent.With the increase of aging time,the effect of pre-strain will gradually weaken and the influence of aging on materials will gradually increase.The correlations between the stress relaxation model considering the molecular chains and the test results were more than 0.9950,which can accurately describe the stress relaxation modulus of HTPB coating during the pre-strain thermal aging process.

Bayesian inference for ammunition demand based on Gompertz distribution

Aiming at the problem that the consumption data of new ammunition is less and the demand is difficult to predict,combined with the law of ammunition consumption under different damage grades,a Bayesian inference method for ammunition demand based on Gompertz distribution is proposed.The Bayesian inference model based on Gompertz distribution is constructed,and the system contribution degree is introduced to determine the weight of the multi-source information.In the case where the prior distribution is known and the distribution of the field data is unknown,the consistency test is performed on the prior information,and the consistency test problem is transformed into the goodness of the fit test problem.Then the Bayesian inference is solved by the Markov chain-Monte Carlo(MCMC)method,and the ammunition demand under different damage grades is gained.The example verifies the accuracy of this method and solves the problem of ammunition demand prediction in the case of insufficient samples.

Joint optimization of inspection-based and age-based preventive maintenance and spare ordering policies for single-unit systems

This paper presents a joint optimization policy of preventive maintenance(PM)and spare ordering for single-unit systems,which deteriorate subject to the delay-time concept with three deterioration stages.PM activities that combine a non-periodic inspection scheme with age-replacement are implemented.When the system is detected to be in the minor defective stage by an inspection for the first time,place an order and shorten the inspection interval.If the system has deteriorated to a severe defective stage,it is either repaired imperfectly or replaced by a new spare.However,an immediate replacement is required once the system fails,the maximal number of imperfect maintenance(IPM)is satisfied or its age reaches to a pre-specified threshold.In consideration of the spare’s availability as needed,there are three types of decisions,i.e.,an immediate or a delayed replacement by a regular ordered spare,an immediate replacement by an expedited ordered spare with a relative higher cost.Then,some mutually independent and exclusive renewal events at the end of a renewal cycle are discussed,and the optimization model of such a joint policy is further developed by minimizing the long-run expected cost rate to find the optimal inspection and age-replacement intervals,and the maximum number of IPM.A Monte-Carlo based integration method is also designed to solve the proposed model.Finally,a numerical example is given to illustrate the proposed joint optimization policy and the performance of the Monte-Carlo based integration method.

Concept and evaluation method of equipment system of systems contribution rate

To scientifically evaluate the equipment system of systems(SoS)contribution rate,a contribution rate calculation method based on a structural equation model(SEM)is proposed in this paper.The connotation and evaluation process of the equipment SoS contribution rate were redefined and standardized.To solve the existing problems in the application of the original contribution rate formula,a modified contribution rate calculation formula is proposed.Finally,the contribution rate evaluation index was divided into latent and explicit variables.The measurement and structural equations in the SEM were used to calculate and analyze the latent variables.The simulation results show that the number of defense lines of air defense weapon equipment has a greater impact on the linear configuration than the group configuration.When the number of K-type air defense weapons is sufficient,the two-layer linear configuration should be adopted with 20 air defense weapon systems.When the number of K-type air defense weapons is insufficient,the single-layer group configuration should be adopted with 12 air defense weapon systems.

Summary of Research Status and Application of MEMS Accelerometers

The rapid development of MEMS technology has made MEMS accelerometers mature and the application range has been expanded. Many kinds of MEMS accelerometers are researched. According to the working principle of MEMS accelerometer, it can be divided into: piezoresistive, piezoelectric, capacitive, tunnel, resonant, electromagnetic, thermocouple, optical, inductive, etc. Due to its outstanding features in terms of size, quality, power consumption and reliability, MEMS sensors are used in military applications and where high environmental resistance is required. MEMS accelerometers are developing rapidly and have good application prospects. In order to make MEMS accelerometers more widely understood, the advantages of MEMS accelerometers are expounded. The research status of MEMS accelerometers is introduced, and MEMS are analyzed. The application of accelerometers in real-world environments, and the development trend of MEMS accelerometers in the future. More scholars will invest in MEMS accelerometer research, pursuing high performance, low power consumption, high precision, multi-function, and interaction. Strong MEMS accelerometers will be ubiquitous in the future.