As for a class of nonlinear discrete systems with unknown parametersa multi-model control method based on the improved BP neural network is proposed.Firstlythe nonlinear system is expressed with a linear part and a nonlinear part.When the nonlinear part has small impact on the systemthe linear robust controller designed based on the fixed model and the adaptive model is directly used to control the system.When the nonlinear part has large impact on the systemthe adaptive control under the improved BP neural network is adopted.Secondlythe switching criterion is used to smoothly switch the control input and the stability of the system is proved.Finallysimulation results show that the proposed method can improve the system control quality and reduce the oscillation of the control signal.

Based on integral sliding mode method and Extended State Observer (ESO)an active fault-tolerant control system is developed to implement position and attitude control of quadrotor UAV with actuator failure.A nonlinear model of UAV with actuator failure is establishedand a Sliding Mode Control (SMC) method with strong disturbance rejection ability is used to design basic controllers for the inner loop of attitude and the outer loop of position.In order to reduce the errors of the steady-state systeman integral sliding mode controller is constructed.The boundary layer method is used to suppress the chattering of SMC algorithmwhile ESO is used to estimate the total internal and external disturbances and the interference of actuator failure in real time and then compensate for the controlled variables.It is verified by Lyapunov stability theory that the flight control system can converge rapidly to a stable stateand the effectiveness and robustness of the developed flight control system are verified by some numerical simulations.

A finite-time adaptive neural tracking control method is proposed for nonlinear pure-feedback systems with input saturation and output constraints.Finite-time control theoryBarrier Lyapunov functionand Radial Basis Function (RBF) neural network are used to design novel virtual and real input signalswhich solves the finite-time control problem of nonlinear pure-feedback systems with input saturation and output constraintsand ensures that the output of the system can track the reference signal within a finite time and the tracking error of the system is limited to a small neighborhood of the origin within a finite time under the condition of satisfying input saturation and output constraints.Finallya simulation experiment has clarified the effectiveness of the designed controller.

In order to control multi-rotor aircraft to hover stably and precisely over a fixed point,position and attitude controllers are designed by using cascade PID to control the position and attitude of the multi-rotor aircraft.A mathematical model is established after kinematics and dynamics analysis of the multi-rotor.Based on the analysis of the modela control allocation model is established.In order to simplify the design of controllersthe controllers are divided into two partsnamelyposition and attitude controller and control allocator.Changing the control allocator can realize the flight control of different rotorswhich has wider applicability.Simulation results show that the multi-rotor UAV has fast response speed with the stages of vertical take-off and level flight connected closelyand can accurately reach the given target point and hover stably over it.

As for the linear systems with multi-source disturbancesa two-level optimal setting control method based on disturbance observer is studied.For the disturbances without a complete and accurate modela disturbance observer is designed.For the norm-bounded external disturbances which cannot be described by the disturbance observera dynamic optimal setting control scheme is provided.According to the observation value of the disturbance observerthe set value is adjusted dynamicallyso that the controlled output can still track the set point under the action of the original controller when there are multi-source disturbances in the system.Numerical simulations have verified the feasibility and effectiveness of this method.

A risk assessment method based on Monte-Carlo is proposed to solve the safety problem of UAV system when entering the integrated airspace to perform different tasks.Firstlythe factors affecting the ground impact events of the UAV system in the fused airspace are analyzed.Thenthe parameter distribution is used to describe the uncertainty of each influencing factor.Finallytwo typical UAVsnamelyFirebird and Typhoon Hare selected to conduct safety assessment using Monte-Carlo simulation algorithm in the low-risk areathe general risk area and the high-risk areaand the sensitivity analysis of each influencing factor is carried out.Simulation shows that different types of UAV system under different operation environment have big differences in safety target leveland UAV falling down angle is the key factor influencing the allowed failure rate.The method provides a feasible way of thinking for operational risk evaluation when UAV system entering the integrated airspaceand can enhance UAV safety level.

It is difficult for a single UAV to attack high-value targets with tight air-defense system.To solve the problemthis paper adopts a saturation attack technology applied to low-cost UAV swarmand proposes a three-stage saturation attack strategy with consensus under cooperative control.Based on the characteristics of tasks at different stagesthe improved consensus algorithm is designed correspondingly for each phase.On the basis of UAV cooperation under multiple conditions in saturation attack tasksDubins curve is introduced to add flight trajectory constraintsso as to smooth UAV flight trajectory and shorten the flying distance.In the mission scenario of high-precision formation keepingan improved second-order consensus controller is designed to ensure flight precision and speed up convergence.Finallythe actual effects of the improved algorithm at each stage is compared with that of the traditional algorithm to verify its effectiveness and extensibility.Simulation results show that the algorithm can be applied to large-scale UAV swarm with satisfying effectswhich provides a basis and reference for the decision makingdeployment and tactical implementation of saturation attack strategies.

Aircraft/Store Electrical Interconnection System (AEIS) needs to be more universalized in the integration of all sorts of domestic aircraft platforms with the stores of large/medium-sizedsmall-sized and miniature weapons.In this papera systematic solution is presented.Firstthe development tendencies of relative technologies and relevant standards of AEIS at home and abroad are described.Thenan analysis is made to the composition of AEIS standard clusters and the evolvement of signal sets.Finallyideas and methods for systematized implementation of AEIS standards are proposed with a brief description of its application prospect.

Fast and Adaptive Bidimensional Empirical Mode Decomposition (FABEMD) is applied to target recognition in Synthetic Aperture Radar (SAR) image.FABEMD could fast decompose SAR images into multiple Bidimensional Intrinsic Mode Functions (BIMF)which can describe the information of targets from low to high frequencies.The index of structural similarity is employed to remove the BIMFs that are contaminated by noisesand the highly discriminative ones are kept.In the classification phase,Joint Sparse Representation (JSR) is used to represent the selected BIMFs.Experiments are conducted on the MSTAR data set to test the proposed method and the results validate its performance superiority.

The traditional Kernel Correlation Filter (KCF) tracking algorithm cannot handle well when the target is moving fast or has large-area occlusionwhich may cause the target to be lost. Based on the traditional KCF algorithmthis paper proposes three mechanismsnamelytarget loss detectionfirst frame re-detection and extended area re-detectionto solve the above problems.The maximum response score and Average Peak Correlation Energy (APCE)are used to determine whether the target is missing.When the target is about to be lostthe extended area re-detection mechanism is adopted. When the target image is similar to the first-frame image of the targetthe first frame re-detection mechanism is adopted. In order to reflect the tracking performance of the proposed algorithm14 sets of video sequences were selected from the VOT2016 and OTB100 data sets as the test setsin which 7 sets of video sequences had the scenarios of target occlusion and fast motion.A quantitative comparative experiment shows thatcompared with the traditional KCF algorithmthe improved algorithm reduces the average Center Position Error (CPE) by 20 pixelsand increases the average Overlapping Rate (OR) by 16.1%.

This paper introduces a novel method that solves the Multi-Pursuer and Single-Evader (MPSE) UAV confrontation problem based on the semi-direct method.Firstlythe theory of the semi-direct method is introduced.In this methodcalculus of variations is used to convert the bilateral optimization problem into a unilateral optimization problemwhich is then converted into a nonlinear programming problem by using Legendre pseudo-spectrum method.The mathematical models of the two sides of the MPSE problem are establishedthe objective functions of the two sides are givenand then the optimal flight path is obtained by using the semi-direct method.Secondlyin Matlab programming environmentthe Snopt tool kit is used for numerical simulationwhich proves the correctnesseffectiveness and rapidity of the algorithm.Finallythe traditional proportional navigation method is used for comparisonwhich verifies the applicability and interoperability of the algorithm.

Ballistic missile is a kind of high-performance offensive weapon.In the process of penetrationit will adopt a series of penetration technologies and form ballistic group targetswhich makes it difficult for our radar to track the target.Thereforehow to stably track ballistic group targets with high precision becomes the key to solve this problem.The idea of ballistic group target tracking is comprehensively introduced.According to the framework of ballistic group target trackingthe realization algorithms of each function unit are summarized.The basic principles and characteristics of the group initiation algorithmthe group combination/separation algorithmand the multiple target tracking algorithm with data association and data non-association are mainly expoundedand the development direction of ballistic group target tracking technology is described from four aspects.

With the extensive application of civil UAV technologythe practice of integrating UAV into national airspaceand executing flight missions with manned aircraft in shared airspace at low altitude has become a trend of future development.UAV “sensing and avoiding” system plays a crucial role in ensuring flight safety in the integrated airspace in the futureand the autonomous collision avoidance algorithm is a key part to ensure efficient operation of the whole system.At presentthe research on autonomous collision avoidance algorithms of the UAV has been very in-depth.The existing collision avoidance algorithms are classified based on the characteristics and mechanism of collision avoidancedifferent types of collision avoidance algorithms are introduced in detailand their advantages and limitations are expounded.Finallythe development direction of autonomous collision avoidance algorithms for UAVs is prospected.

Infrared Search and Tracking (IRST) system has become one of the main equipment for battlefield perception owing to its advantages such as strong anti-EMI (Electromagnetic Interference) abilitypassive detectionperfect concealmenthigh positioning accuracyand strong ability to detect stealth targets.However limited by its own detection mechanismIRST has such problems as incomplete dimension of detected informationlong search durationlow data update rateand susceptibility to clouds.According to the working principle of IRSTthe characteristics of it in target detection are analyzed.The mainstream target motion model in maneuvering target tracking is introducedand three kinds of traditional Multi-Target Tracking (MTT) technologies are introducedwhich are MTT based on Joint Probabilistic Data Association (JPDA) MTT based on Random Finite Sets (RFS) and MTT based on deep learning.Finallythe prospect of MTT technologies is given.

The target-borne equipment of missile miss distance measurement systems is easily damagedand current mainstream missile miss distance measurement systems are expensive and cumbersome.In view of the above problemsthe development trend of missile miss distance measurement is analyzed.A few miss distance measurement methods and their technological advances in recent years are analyzedin which a method with the greatest application potential is obtained.The study is of great significance for improving current missile miss distance measurement systems and enhancing the performance of missile miss distance measurement.

The dynamics boundary and its protection strategy for landing when aircraft system failure occurs is studied.The longitudinal dynamics model of an aircraft under system failure is established with a certain transport aircraft as the research object.To solve the problem that the failure of the system may lead to loss of control in flighta dynamics boundary determination method based on the reachability set theory is proposedand then the situations of elevator jamming and thrust loss are analyzed respectively.In order to ensure the safety of landing under system failurea dynamics boundary protection system is designed and the effectiveness of the system is verified through dynamics simulation.The research results can provide a new idea for the design of boundary protection systems for aircraft landing.

The existing LDPC code open set recognition algorithm uses the code length and the starting point of the code word as known conditions for recognitionwhich limits the practical application of the algorithm.In order to overcome this shortcomingthis paper proposes a code length and code word starting point recognition algorithm based on the minimum error judgment criterion.Firstthe received sequence is intercepted according to the estimated value of the code length and the code word starting point to construct a code word analysis matrixand then Gaussian column transformation is conducted on the analysis matrix and possible check vectors are obtained.The LDPC code check vector is further selected based on the minimum error judgment criterionand finally the maximum number of check vectors at different traversal values of code lengths and code word starting point is foundso as to realize code length and code word starting point identification.The simulation experiment results show that when the bit error rate is on the level of 10-3the recognition rate of the algorithm reaches 100% for the LDPC code under the IEEE802.16E protocol.

After completion of a planting protection operationthe UAV needs to land autonomously.The landing of conventional UAVs is usually assisted by their own GPS systembut big errors will occur when the system is applied to small UAVs in precise positioning.To address this issuefor the situation when the UAV needs to land at a fixed pointa fixed-point recognition method based on the machine vision system is studied.Firstlya specific landmark is set as the fixed pointand different color values in the image captured by the machine vision system are extracted.After color value extractionexcept the color of the fixed pointthe interference information of all the other colors is filtered.Thenthe shape information of all the elements in the image is analyzed.After the shape analysisall the elements whose shape doesnt accord with the shape of the fixed point are excluded.The contour of the landmark is identified through Canny edge detection.A plane coordinate system is set upand the specific location of the landmark in the coordinate system is calculated by using the pixel information obtained from edge detection.Finallyexperimental results show that the machine vision system can assist the UAV to precisely land at the fixed point.

Firstthe characteristics of laser phase noise under different laser linewidth conditions are analyzed.Thena theoretical model of the influence of laser phase noise on detection performance of coherent lidar is established.Finallythe influence of laser phase noise on performance of coherent lidar is analyzed by statistical simulation specific to two typical cases including pulse coherent lidar and FMCW coherent lidar.The research results show that:1) In the case of pulsed laserthe influence of laser phase noise on detection performance has little relationship with detection rangeso it is unnecessary to restrict the detection range to be less than the coherent length;and 2) In the case of FMCW coherent lidarthe detection performance is much susceptible to laser phase noiseso it is necessary to restrict the detection range to be less than the coherent length with one order of magnitude.

Aiming at the safety failure accident caused by the system dependency relationshipthis paper constructs a system safety network based on the dependency relationship according to the logic of “liveware-environment-software-hardware”and analyzes the mechanism of emergent failure of safety.A system safety network framework based on interaction behavior is establishedand the method of Functional Dependency Network Analysis (FDNA) is improved accordingly.Cascading failure is used to characterize the emergent failureand a numerical simulation method of emergent failure of aircraft system safety based on cascading failure is proposed.The evolution relationship between system components and interaction behavior is analyzed.The network damage mode under different failure modes is obtained.The simulation results show that：1) The emergent failure process of aircraft system safety needs to consider both the topology and the safety benefits；and 2) Emergent failure of safety can have a serious impact on system safety performance.

In order to detect weak targets on sea surface in the background of strong sea cluttera detection algorithm based on optimized ESMD-ICA is proposed.The wavelet modulus maxima denoising algorithm is used to denoise the signalthen the ESMD-ICA denoising algorithm is optimizedand finally the ELM model improved by Gray Wolf Optimization (GWO) is used to predict the reconstructed denoised signal.IPIX radar measurement data is used to verify the new algorithm.The experimental results show that the new algorithm does not destroy the chaotic property of the signal under the premise of suppressing sea clutterand the detection performance of the new prediction model is much better than that of the traditional prediction model (BP neural network).The new algorithm performs well in denoising effectmodel training and detecting timedetector stability and so onwhich is conducive to its wide application in practical engineering.

Global Navigation Satellite System (GNSS) has become the most popular apparatus for generating navigation and positioning informationand ground vehiclessmartphones et al all rely on GNSS for obtaining high-precision navigation and positioning information.Howeverunder complex city environmentsGNSS signals are often blocked by the surroundingsand thus the GNSS receiver cant obtain adequate signalswhich may lead to big positioning errors or no output of navigation solutions.Vector Tracking Loops (VTL) use a Kalman filter to estimate the navigation and positioning solutionsand VTL is able to output positioning information with only one visible satellite.Howeverthe positioning errors will diverge over time.In order to improve the VTL performance under signal challenging environmentsthis paper proposes an altitude information aided VTL methodand the model is given.Field tests show that the positioning errors are obviously reduced in the two-minute experiment with the aid of altitude information.

ARINC818 is widely applied in aircraft systems both at home and abroad due to its high bandwidthlow latencynon-compressed Digital Video Interface (DVI)strong anti-EMI (Electromagnetic Interference) ability and light weight.There are high requirements on the safety of avionics systemsso a high-security design of ARINC818 has become one of the most important considerations in airworthiness certification.This paper proposes a high-security design of ARINC818whose validity and feasibility are proved by fault injection and other tests.