In image matching, higher resolution of an image means higher matching accuracy and there are more features that can be extracted, but the matching time is longer.Thus, the image matching algorithm based on SIFT is improved in this paper.Rough matching is performed on the feature points of the second group of Gaussian pyramids.The improved RANSAC based on GMS is used to eliminate the mismatched points and obtain the affine matrix, and the matching area is roughly determined.During the process of accurate matching, the remaining feature points in the same matching area are filtered, and the matching pairs are filtered by using the previous affine matrix, and the least squares algorithm is used to eliminate the mismatched points again and quickly solve the final affine matrix.The experimental results show that this method greatly shortens the matching time and improves real-time performance under the condition of guaranteeing the sub-pixel accuracy.

Conflict evidence reasoning is an important research subject of uncertain reasoning.There are many ways to effectively combine conflict evidences by using the revised data source.However, the formula describing the distance between the evidences used to modify the evidence source is complicated, and the flow of the algorithm is also complicated.The algorithm does not probe into the combination rule of the time-sequence evidences.In response to these problems, a fast algorithm for conflict evidence reasoning is proposed.Firstly, a new evidence measurement formula is proposed, and the validity and calculation amount of the evidence measurement formula are analyzed.Then, the general flow of the new algorithm is given, and the parameters in the flow are analyzed and determined.Finally, The algorithmic steps of the combination rule of the time-sequence evidences are given and the effectiveness of the algorithm is verified by example analysis.

A new threat assessment method for Beyond-Visual-Range(BVR) air combat is proposed taking capability threat, situation threat and intention threat into consideration.Firstly, the first-shot capability threat model and the attack threat model of the BVR air-to-air missile are added to the capability threat model.Secondly, the situation threat is modified by the situation validation factor and the missile-guidance validation factor.A new situation threat calculation method is given.Then, the target maneuvering recognition and situation prediction are carried out based on the Hidden Markov Model (HMM) and then an intention threat modeling method is proposed.At last, a simulation is carried out on the comprehensive threat assessment model, which proves that the proposed method is effective in BVR air combat.

In order to solve the problem that some satellites are not sensitive in the fault detection algorithm, a Slope-Weighted Least Square (SWLS) algorithm is proposed.This method theoretically derives the expression of the satellite feature slope, constructs the slope-weighted matrix according to the size of the feature slope, and gives greater weight to the satellite with smaller feature slope.The slope-weighted test statistics are constructed, and the satellite fault detection is realized by comparing the new test statistics with the detection threshold.This method is verified by using real data, and the results show that the fault detection rate of the slope-weighted least square RAIM algorithm is better than that of the least square RAIM algorithm.

To solve the problem of time-varying formation control of the second-order multi-UAV system, a consensus distributed controller is designed by using the event-triggered function, so that the multiple UAVs can form a time-varying formation.The Laplacian matrix is decomposed considering its special properties.The formation problem is simplified to the problem of asymptotic stability of low-order systems.The algorithm of controller design is given.Linear Matrix Inequality (LMI) and Lyapunov function are used to prove the effectiveness of the algorithm under the given event-triggered function.It is proved that there is no Zeno phenomenon in the time sequence of the given event-triggered function.The motion of the multiple UAVs system is simulated in 3D space.The results show that the multiple UAVs can form the desired time-varying formation under the effects of the designed controller, which effectively saves communication bandwidth and computing resources.

In the bistatic radar, the unsynchronized clock source will bring carrier frequency deviation and time synchronization error to the received signal, which may affect the accurate positioning and slow micro-Doppler detection.Aiming at these factors, a combined processing algorithm is proposed based on phase compensation of direct wave phase and frequency-domain cancellation of the range Doppler spectrum.The algorithm does not need a shared clock source for the bistatic system.Firstly, all received signals are Scompensated by the phase of the direct wave to offset the phase error caused by carrier frequency deviation.Then, the side-peak interference caused by the time synchronization error is effectively eliminated by frequency-domain cancellation using the data of range Doppler spectrum.This algorithm has low complexity and is easy to implement.The validity of the algorithm is verified by theoretical derivation and experiments.

To solve the problem of formation containment control of multi-UAV system with several leaders under joint connected topology, distributed consensus controllers for leaders and followers are designed respectively.The Laplacian matrix is partitioned according to the leaders and followers.The Laplacian matrix with the directed spanning tree is decomposed, and the problem of formation control of the leader is simplified to the problem of asymptotic stability of the low-order time-varying system.The amount of control error is defined in the follower implementation, and the problem of containment control of the follower is simplified to the problem of asymptotic stability of the time-varying system.The averaging method is used, and the asymptotic stability of the two time-varying systems is transformed into that of two time-averaged systems.The design steps of the controller are given by using Linear Matrix Inequality (LMI) and Lyapunov function.The communication topology switching of the multi-UAV system is fast enough for the system to realize formation containment control under the condition of joint connected topology.The simulation results prove the effectiveness of the designed controller.

The covariance intersection algorithm is a distributed fusion estimation method obtained by optimizing certain objective functions, which provides a new idea for image fusion enhancement.An image fusion method based on the Covariance Intersection(CI) algorithm and the local gradient extrema based Bidimensional Empirical Mode Decomposition(BEMD) is proposed.To overcome the inadequacy of traditional BEMD in obtaining image details and to include more detailed structure features in the image, according to the strong ability of the gradient to mine the detailed information of the image, local gradient extrema are selected by using four two-dimensional extremum conditions.Then, empirical mode decomposition of the image is carried out and the IMF is determined.Then, the one-dimensional covariance intersection algorithm is extended to 2D signals and image fusion.The optimal linear weighting matrix is computed by minimizing the F-norm of the 2D covariance intersection matrix of each IMF.The enhanced fusion image is obtained by using inverse reconstruction.The simulation results show that, compared with the traditional image fusion algorithm, the proposed method has stronger detail capture ability and better clarity.

To solve the problem of parameter perturbation and uncertainty in the flying process of fixed-wing UAV formation, a robust control method for the leader-follower UAV formation based on adaptive disturbance observer is designed.The leader-follower UAV formation model and the UAV motion model are established, and the properties of the adaptive law of discontinuous projection are demonstrated.Then, the robust control law for the inner loop is designed to track the command signal produced by the outer-loop formation controller.In the design process of the robust control law, the adaptive law for the parameters is introduced to online estimate the parameter perturbation, the adaptive disturbance observer is designed to observe and compensate for the uncertainties, and the stability analysis is given by using the Lyapunov function.Finally, simulation results demonstrate the effectiveness of the proposed method in the robust control of UAV formations.

To solve the fault-tolerant control problem of uncertainty, control surface faults and saturation for Reusable Launch Vehicles (RLVs) during reentry, a back-stepping control strategy based on Fixed-Time Disturbance Observer (FTDO) combined with auxiliary anti-saturation system is proposed.Firstly, a FTDO based on the super twisting theory is designed, which not only ensures the accurate estimation of disturbance, uncertainty and actuator faults in the system, but also effectively improves the estimation accuracy of the disturbance with variable frequencies.Secondly, an auxiliary compensation system based on anti-windup technology is devised to make the control surfaces exit saturation state as soon as possible, so as to tackle the problem that the control surfaces are liable to be saturated during RLV reentry.The simulation results show that the fault-tolerant control method can effectively solve the problems of faults and saturation of control surfaces, suppress disturbances and uncertainties, and improve the control accuracy and robustness of the attitude control system during RLV reentry.

Based on the principle of power synthesis of coherent signals in the intersection area of the distributed array, a mathematical model of coherent signal synthesis in the distributed array is established.On the basis of this model, power resource optimization problem of the bi-linear vertical crossing array is modeled.Based on this optimization model, computer simulations are carried out according to whether there are phase errors in the signals arriving at the intersection area.The SQP algorithm and the genetic algorithm are used to find the optimal solution of power allocation, and the optimal power allocation scheme is obtained.The optimization can not only improve the effect of signal synthesis, but also provide a solution and theoretical basis for the optimization of power resources in coherent signal synthesis of the distributed array.

To solve the problem of boundary oscillation and difficulty in realizing the fission of the classic algorithm for multi-agent system motion control based on the principle of Separation, Alignment and Cohesion (SAC), a motion control algorithm based on attention-following mechanism and Focus-Improved Artificial Physics (F-IAP) is proposed.The alignment area and the aggregation area of the classical SAC algorithm are combined in this algorithm, and the gravitational coefficient is adjusted according to the distance and the speed, so as to change the effects of the mimic physical force.The problem of boundary oscillation of the SAC algorithm is solved, and the cohesion, alignment and obstacle avoidance of the multi-agent system are realized.According to the characteristics of biological attention in neuroscience, the agent that directly perceives environmental stimulation is selected as the follow-up object.By using the IAP algorithm, the fission of the multi-agent system is realized in multi-objective environment.The feasibility of the algorithm and the superiority of its performance are verified in simulation.

In order to solve the problem of collaborative search of anti-radiation UAVs, the cost index of collaborative search route planning, which is “all-time-domain field-of-view coverage”, is established.Taking two UAVs as an example, the collaborative search route is planned, and an appropriate collaborative search strategy is formulated.Then, the first-order consensus algorithm is used to coordinate and control the speed of each anti-radiation UAV, so that the anti-radiation UAVs can arrive at the designated position at the same time.The effectiveness and feasibility of this method are verified by simulation.

In order to effectively improve the detection accuracy of the radar, a calibration method based on fitted partitioning under non-uniform distribution of system errors is proposed.Firstly, spatio-temporal alignment between the marine multi-target information obtained by the radar and the truth data provided by Automatic Identification System (AIS) as well as correlative processing are carried out, and the error sequence is obtained.Furthermore, the assumption of system error distribution based on two non-uniform distribution modes is given.On the basis of the rationality of the assumption, the coverage area of radar detection is divided by fitting processing.The estimated value of system errors is obtained, and it is used for the calibration of the radar.Finally, the experiment proves the effectiveness of the method.

In the multi-target tracking process of networked radars, reasonable allocation of radar beams and power resources can further improve the working efficiency of the radar. In order to reasonably allocate radar beam resources, a networked radar resource allocation algorithm based on passive sensor coordination is proposed.The algorithm preferentially uses passive sensors to track targets, compares the predicted target covariance with the covariance threshold, and uses radar to track the targets whose covariance is larger than the threshold. At the same time, according to the targets threat degree to each radar, the target to be tracked is adaptively assigned to the radar, and the Bayesian Cramer-Rao Lower Boundary (BCRLB) trace is used as the cost function to construct a model to predict the optimal power assignment of each radar. The simulation results show that the proposed algorithm can effectively optimize radar resources and has better tracking performance.

The reconstruction and recovery strategies aiming at the control units of the triple-redundancy flight control computer are studied. The redundancy architecture of the flight control computer is briefly introduced. The reconstruction strategy of the control unit is designed by combining self-detection with mutual detection. And then, the recovery strategy of the control unit is designed by reasonably screening the recovery data and formulating the recovery protocol. Finally, a semi-physical simulation platform is built to verify the validity and correctness of the reconstruction and recovery strategies, which improves the reliability of the triple-redundancy flight control computer.

A Synthetic Aperture Radar (SAR) target recognition method in multi-view SAR images is proposed in consideration of both independency and correlation.Due to the azimuth sensitivity of SAR images, the correlations among the multi-view SAR images for recognition are not stable enough.Therefore, the multi-view SAR images are first clustered into several sets based on image correlation.Images in each set share relatively high correlations.Afterwards, Joint Sparse Representation (JSR) is employed to jointly reconstruct the multi-view SAR images in each view set and produces the reconstruction errors with high precision.Finally, the linear weighting strategy is used to fuse the reconstruction errors from different view sets to determine the target label.Experiment tests are carried out on the MSTAR dataset.The results prove the effectiveness of the proposed method.

Aerial Moving Target Indication (AMTI) carried out by the space-based early warning radar has great significance in military applications.However, when confronted with severe range ambiguities and Doppler ambiguities, the conventional Linear Frequency Modulation (LFM) waveform has low data search rate, few coherent pulses, and weak clutter-suppression and anti-jamming capabilities.In this paper, the design requirements of the synthetic wideband waveform for space-based AMTI radar detection at near, middle and far range are researched on the basis of the American project known as L-band Lightweight Space Based Radar (LLSBR).The simulation results of synthetic wideband signal processing show that the synthetic wideband waveform has excellent performance in the detection of high-speed weak aerial targets for space-based AMTI radars.

For the optical system with a cooled long-wave infrared detector, a secondary imaging convergence system with three germanium lenses is designed.An optimal design method of a low-noise refractive infrared optical system is proposed, and the method is compared with the traditional optimal design method for stray radiation suppression.Simulation analysis is carried out by using Tracepro.The results show that, compared with the traditional method, the new low-noise design method improves the stray radiation suppression effects by 23.87%.

Deu to the distinctive flight characteristics of high-performance aircrafts, the models have strong non-linearity and the parameters have strong coupling, which brings a challenge to the design of flight controllers.When designing the controller of the nonlinear system, the traditional method of sliding mode control has the advantages of easy implementation and strong robustness, but the chattering of system states is likely to appear, which may weaken the efficiency of the controller.To solve the above problems, a sliding mode controller with unidirectional auxiliary surface based on the fast double-power reaching law is proposed, and the conditions of convergence are proved.The longitudinal model of the aircraft is divided into four control loops, which are the loops of altitude, velocity, attitude angle and angular speed of attitude, and the controller for each loop is designed respectively.Simulation results show that the proposed design method of flight controllers can effectively control the longitudinal state of the aircraft, and can effectively suppress the chattering.

In order to reduce the influence of disturbance torque variation on Seeker Servo Control System (SSCS), an adaptive Internal Model Control (IMC) scheme based on disturbance torque estimation is proposed.Firstly, the mathematic model of the SSCS is established, and an internal model controller is designed.The change of the rotating inertia of the SSCS is identified by using the method of disturbance torque estimation.According to the change of the rotating inertia, the parameters of the internal model controller are adjusted automatically by the linear adaptive rate to ensure the control performance of the controller.The simulation and experimental results show that the control scheme has strong adaptability to the change of system working conditions, which improves the anti-interference performance and robustness of the SSCS, and achieves good control effects.