In the environment with small Radar-Cross Section (RCS), serious clutter and noise, it is difficult to detect the slow-moving target at short range. To solve the problem, a target detection method based on double-channel convolutional auto-encoder with skip connection is proposed. The time-frequency spectrum is introduced to the convolutional auto-encoder as the input. The neural network structure adopts the IQ double-channel to extract amplitude features and phase features from target echoes, and fuses the multi-dimensional features in the middle layer. Considering that the target scale is small in time-frequency spectrum, the skip connection structure is designed in the network, which connects the top and the bottom of the network to improve the recovery ability of target feature in decoders. Moreover, it can mitigate the gradient dissipation problem of the deep network, and improve the efficiency of end-to-end training. Experimental results show that: In the environment with serious clutter and noise, this method can achieve better performance on detection of small, slow-moving target than the traditional methods.

For a class of uncertain nonlinear systems, a new adaptive output feedback control method combining backstepping with active disturbance rejection control is investigated.By introducing the Extended State Observer (ESO), the unknown state of the controlled system is estimated in real time.At the same time, the ESO is used to implement online approximation and compensation of the uncertain terms in the system.The nonlinear filter is used to differentiate the virtual control signal during the backstepping design process, which avoids the complexity explosion problem in the traditional backstepping design control, and an adaptive output feedback controller is designed accordingly.The stability of this control method is proved by Lyapunov function, and it is verified that all signals in the closed-loop system are bounded.Numerical simulation examples further verify the effectiveness of the method.

In view of the serious nonlinearity, the multivariable coupling and parameter uncertainty in the nonlinear dynamic system of rotating rocket projectiles, an Improved Nonlinear Disturbance Observer (INDO) is proposed to observe the approximating feature of the disturbance of high-frequency motion.A backstepping sliding mode controller is designed by combining with the backstepping sliding mode control.And the stability of the system is proved. Finally, the performance of the Traditional Nonlinear Disturbance Observer (INDO) is compared with that of the improved observer.The simulation results show that the improved observer has higher estimation accuracy and stronger robustness.

Quantitative measurement of the complexity of electromagnetic environment of the reconnaissance pod is an important step for constructing a realistic battlefield environment.In order to solve the problem of the quantitative measurement of the complexity of electromagnetic environment in which the reconnaissance pod is located, an analysis is made to the electromagnetic environment.Starting from main factors that cause the complexity of electromagnetic environment, combining the objectivity and subjectivity of environmental complexity factors, an algorithm that solves the quantitative measurement of the complexity of electromagnetic environment is obtained based on gray Analytic Hierarchy Process (AHP) method and combination theory.Based on this algorithm, the principle of complexity equivalent replacement is proposed to further simplify algorithm calculation.Finally, the algorithm is verified through a typical radar electromagnetic environment, and the software is formed through LabWindows CVI.Experimental results show that the proposed algorithm has certain practical significance for measuring the complexity of a complex electromagnetic environment.

In order to enhance the transient performance and precision of the quadrotor Unmanned Aerial Vehicle (UAV) in target tracking, a new non-singular, fixed-time sliding mode control method is proposed with Image-Based Visual Servoing (IBVS), which realizes precise fixed-time tracking of the speed and attitude commands of the quadrotor UAV.Firstly, the virtual image plane is established through perspective projection, and the dynamics model of the quadrotor UAV is deduced by using the image moment features.Based on fixed-time stability theory, a novel fixed-time sliding mode surface is presented, which supplies an accurate method for estimating convergence time.Based on the position loop and attitude loop of the UAV dynamics model, the non-singular, fixed-time sliding mode controllers are designed respectively, and the stability of the system is proved by using Lyapunov method.Numerical simulation results show that the designed controller can not only avoid the overshoot problems and reduce the steady state error, but also has strong robustness.

The combination of path planning and tracking is one of the solutions for Unmanned Aerial Vehicles (UAVs) to perform terrain following tasks.According to the terrain elevation data, the optimal flight path planning of terrain following can be transformed into a quadratic programming.The vector field method is used as the guidance strategy, the feasible vector field parameters are designed, and the path following controller is designed with the flight path angle of the aircraft as the controlled output.Simulation verifies that: 1) The planning results meet the predetermined safe altitude requirements of terrain following and aircraft maneuverability constraints;2) The proposed guidance strategy has accurate and reliable path tracking capabilities;and 3) The UAV can implement the terrain following task effectively by using the proposed method.

In order to improve the accuracy of ballistic missile midcourse recognition, an event decision-making method based on Case-Based Reasoning (CBR) is proposed.First of all,according to the actual situation, the requirements of ballistic missile midcourse recognition is analyzed reasonably, and the frame representation method is used to categorize the ballistic missile attack scenario according to their different attributes, and the different attributes are weighted according to specific cases.After that,the similarity of different attributes is calculated to match the most suitable plan.The tested plan can be directly used to guide the actual combat after simple adjustment.Finally,an example is given to verify the proposed method, which has proved its feasibility.

In the area where the geomagnetic change is slow, the one-dimensional geomagnetic matching navigation has a low matching probability and limited application range.Aiming at the problem, a multi-dimensional geomagnetic matching algorithm based on PSO is proposed for aircraft networking flight.Based on the single-dimensional geomagnetic matching model, a master-slave networking geomagnetic matching model is established.Using multiple aircraft space constraints, the average absolute error rule is extended from one-dimensional calculation to high-dimensional matching.The positioning effectiveness is evaluated from three aspects of successful matching rate, matching error and algorithm fitness.Simulation results show that the multi-dimensional geomagnetic matching can obtain higher matching probability and matching positioning accuracy in a short period, with a matching rate 10% higher than that of single-dimensional geomagnetic matching at the same matching point.

In order to improve the hit accuracy of TV terminal guidance projectile to the ground target, reduce the falling angle error of the projectile, and realize the goal of hitting the target at a desired falling angle, a sliding mode guidance law combining means clustering with RBF neural network is proposed, for which an analysis is made to characteristics of sliding mode guidance law with falling angle constraint, and the shortage of Radial Basis Function (RBF) neural network sliding mode guidance law that is difficult to hit the target at the desired falling angle is taken into consideration.The new guidance law enables the neural network to adjust the clustering center and center value continuously according to the real-time flight state of the projectile in the learning process, and make the center value be always the optimal solution in the current flight state, thus to realize the optimization of guidance law.Numerical simulation is made to static target and moving target.The results show that, compared with sliding mode control with falling angle constraint and RBF neural network sliding mode control, the proposed guidance law can make the projectile hit the target at the desired falling angle, and is more robust.

The eigen-projection matrix processing algorithm can be used to maintain the mainlobe pattern while suppressing sidelobe interference.However, the performance is significantly reduced in the situation that the power of the mainlobe interference is on the same level as the sidelobe jamming.In order to solve this problem, a new method is proposed by reconstructing the mainlobe interference eigenvector space.Different methods are used for calculating the eigenvectors corresponding to the strong and weak mainlobe interferences, which jointly construct the mainlobe interference eigenvector space.Then, the covariance matrix is pre-processed by the eigen-projection matrix, and the adaptive weight vector is calculated according to the MVDR criterion.Simulation result shows that: the algorithm effectively maintain the mainlobe pattern while suppressing sidelobe interference when there are both strong and weak mainlobe interferences.

A robust fault-tolerant control method is proposed for the quad-rotor Unmanned Aerial Vehicle(UAV) under input constraints with actuator failure and disturbances.Firstly, the position model and attitude model of quad-rotor UAV including actuator fault, input constraints and external interference are established.Then, the position loop and attitude loop are analyzed respectively, and the virtual control command is filtered by sliding mode filter.The uncertainty is estimated by fuzzy system approximation method, and the robust fault-tolerant control law is designed.Finally, the stability of the position loop and the attitude loop is proved.The simulation results show that the proposed robust fault-tolerant control method can quickly and accurately track the command signal under input constraints, and has better control effects than integral sliding mode fault-tolerant control law, which realizes the full-state robust fault-tolerant control including actuator fault and external interference.

In the mobile space optical communication, the fast capture of laser spot center is very important, but it is difficult to satisfy the requirement by using the traditional grayscale gravity center algorithm.In this paper, an optimization scheme is proposed.Filtering de-noising and adaptive binaryzation threshold processing are added before calculating the spot center, which can effectively improve the anti-interference performance of the system.The speed and accuracy of spot center detection are improved by coarse identification of spot center and gravity center calculation.Experiments show that, compared with the traditional grayscale gravity center algorithm, the improved scheme proposed here increases the measurement accuracy and operation speed by an order of magnitude, and has stronger anti-interference ability.

With the increase in the number and types of airborne weapons, plug-and-play weapon integration technology has become a key technology for the development of the new generation of fighters.This article summarizes the technical basis, implementation principles and application status of the two main plug-and-play weapon integration methods in foreign countries, Universal Armament Interface (UAI) and Model Driven Architecture (MDA), and analyzes the relationship between the two methods.Based on this, and according to the current development status of domestic weapon integration, some suggestions are given on the future development direction of domestic airborne weapon integration field.

The centerline surveillance system can provide assistant decision making on carrier gliding slope deviations for Landing Signal Officers (LSOs).Aiming at the deployment of the centerline surveillance system in ordinary airport for Field Carrier Landing Practice (FCLP), the method of mobile deployment and offset installation is proposed based on analysis to the LSO centerline surveillance assistant decision-making principles.By establishing the crosshair model of gliding slope, the issues of high-precision measurement and indication of offset centerline are solved.The architecture of the system is designed and simulation is made.The results show that: 1) The designed system can provide the deviation between the flight path and the ideal gliding slope for the LSO;2) Both the gliding slope indication and the indication accuracy meet the requirements;and 3) The system is flexible for deployment,economic in cost, and convenient to use.

In order to improve the stability accuracy and anti-interference ability of the photoelectric stabilization platform under the application of Linear Active Disturbance Rejection Controller(LADRC), a Variable-domain Fuzzy Active Disturbance Rejection Control (VFADRC) method is proposed.In the case of unknown system models, a fuzzy controller that does not rely on model information is introduced into the design of LADRC.The variable factor function is used to implement variable-domain design.The VFADRC is compared with the LADRC and Model-based Active Disturbance Rejection Controller (MLADRC) methods.The simulation results show that: The designed VFADRC has the advantages of short adjustment time and small overshoot;and 2) The anti-disturbance performance is improved greatly, which can effectively improve the interference suppression capability of the photoelectric stable platform.

The phenomenon of absorption and scattering exists in underwater propagation of light, which may lead to the color distortion and low contrast of the underwater images.For this reason, an underwater image enhancement algorithm based on dark channel prior and Gamma transform is proposed.First of all, the underwater image transmittance and atmospheric illumination are estimated by dark channel prior in RGB space, and the adaptive compensation parameters are obtained after weighted processing.Then, the image color is corrected.On this basis, the enhanced RGB image is transformed into HSV color space, and adaptive Gamma transform is carried out to the V-channel, thus to improve the contrast of the image.Finally, experiments are carried out on the public underwater image enhancement dataset of RUIE, and comparison is made with the existing enhancement algorithms.The experimental results show that the proposed algorithm significantly improves the visual quality of underwater images and is better than the other algorithms.

Path planning is an important part of the objective of UAV task.Considering that the Particle Swarm Optimization (PSO) algorithm is fast in convergence in the early stage and easy to fall into local optimum in the later stage, an improved PSO combined with the Beetle Antennae Search algorithm is proposed, which is applied to three-dimensional path planning of UAVs.In the improved PSO algorithm, by using the advantage of the individual beetle, which has its own judgment on the environment space in each iteration, the path is more reasonable and the search efficiency is higher.The simulation results show that: Compared with PSO, the three-dimensional path planning of UAV based on improved PSO is more effective with less cost.

Infrared sensitivity testing technology is used to quantitatively detect the operating distance of airborne electro-optical targeting system.In order to test and evaluate the ability of the multispectral electro-optical detecting system for searching and tracking infrared targets in middle/long distance under infield condition, an optical measurement system is designed for simulating infrared target heat source and outputting infrared irradiance quantitatively.The blackbody cavity structure and heating power are calculated according to the blackbody classic emission theory.Cassegrain-type reflection system is used to collimate and converge the optical structure to the infrared light path.The parameter relationship between the target infrared radiation characteristics and the diaphragm apertures is established, thus to test and evaluate such performance parameters as operating distance, detection sensitivity and tracking sensitivity of the electro-optical system quantitatively.The test results show that, the optical measurement system can effectively simulate the infrared target at a distance of 5～100 km, accurately calibrate the aperture diameters corresponding to 6 sets of simulated operating distances, and stably output the infrared irradiance in the response band of the electro-optical system.The infrared sensitivity test of airborne electro-optical targeting system is realized.

Aiming at the problem of low navigation accuracy caused by the complex road environment and the influence of the surrounding buildings in the military base or warehouse, an auxiliary vehicle integrated navigation scheme based on Radio Frequency Identification (RFID) is proposed.The corresponding mathematical model is constructed.The RFID can modify the position information calculated by GPS in combined navigation system, which plays an auxiliary role in navigation.Finally, simulation experiment is made on Matlab.The experimental results show that the position error of the target vehicle is effectively suppressed under the assistance of RFID.The auxiliary navigation system can improve the accuracy and reliability of the integrated navigation system and meet the requirements of high-precision positioning of military transport vehicles.

The Bidimensional Variational Mode Decomposition (BVMD) is applied to Synthetic Aperture Radar (SAR) image feature extraction and target recognition.Multiple components are generated after BVMD of the original SAR image, which can effectively describe the global and local information of the target.In the phase of the decision-making, the Support Vector Machine (SVM) is adopted to classify the original SAR image and its decompositions separately.Afterwards, linear weighted fusion is employed to combine their results.Finally, based on the fused results, the target label of the test sample can be determined.The proposed method is tested based on the MSTAR dataset respectively under standard operating condition, with pitch angle variation, and with noise interference, which are compared with several existing SAR target recognition methods.The experimental results verify the effectiveness of the proposed method.

Reuse of software data from different sources to civil aircraft airborne software and the different reuse methods may have impact on the full compliance of airborne software.To achieve cost and risk reduction in software reuse project, the classification of civil aircraft airborne software reuse is made and the software reuse assessment elements are given at first.Then, the software reuse assessment framework and process are established, and the assessment activities and sequences are specified.Finally, the airborne software reuse requirements are given from the perspective of actual certification, and one example of software reuse assessment and certification is presented.The study provides a support for the recognition and assessment of software reuse, and for making certification strategy of software reuse in the early stage of project.

In view of the problem of poor versatility of traditional program loading schemes after the localization and miniaturization of hardware modules of integrated electronic systems, a universal method is proposed for remote loading of embedded processor programs based on virtual parallel NOR FLASH technology.The method uses the board-level management FPGA to store the remote program to be loaded into the external DDR through the SRIO, and makes the program stored in the DDR into the same data format and interface timing as the parallel NOR FLASH through the dual-port RAM and virtual parallel NOR FLASH interface.Therefore, the embedded processor can load remote programs in master parallel mode.The actual results of engineering application show that the proposed method has fast loading speed, and can be universally used between different embedded processors.