The elements of the maneuver form the basis for the tactical maneuver planning.In this paper, the elements of the tactical maneuver in kinetic space are analyzed from such aspects as goal directness of the maneuvering, movement feature and time constraints of the combat platform, and the gains and losses of the combat.Based on the movement characteristics of the combat forces in cyberspace and the characteristics of carrying space, the specific elements of tactical maneuver in cyberspace are given.

Aiming at the problem of UAV path planning, a 3D path planning method is proposed based on the parallel neural network structure and the dynamic adjustable step size strategy.Firstly, different strategies are adopted according to the distance between the UAV and the threat.When the UAV is outside the risk area, the method of taking large steps is adopted to achieve the purpose of rapid generation of the path.When the UAV is inside the risk area, the method of taking the adjustable step is used to achieve the fine search of the path.Then, the neural network of the obstacles penalty function and the energy function of the path are constructed.By combining the gradient descent method with the Newton Downhill Method, the motion equation of the path is established.According to different path points, learning rates with different adaptive learning factors are used to realize rapid escaping from the threats.The simulation results show that the proposed algorithm not only guarantees the safety of UAV to bypass the threat, but also improves the convergence speed of the algorithm.

An online adaptive optimal control scheme based on identification-evaluation architecture is presented for the optimal coordination control of uncertain, non-linear, multi-agent systems.In light of systematic uncertainty, an identification Neural Network (NN) is utilized to each agent to approximate the uncertain system dynamics, and an evaluation NN is used to estimate the solution of the coupled Hamilton-Jacobi (HJ) equations.Then, the optimal control law can be derived.Based on the developed architecture, the weights of the identification NN and the evaluation NN can be updated synchronously. By using Lyapunov's direct method, it is guaranteed that the weight errors of the identification NN and the evaluation NN are uniformly and ultimately bounded, and that the closed-loop system is stable.Finally, a numerical example is provided to demonstrate the effectiveness of the proposed control scheme.

An online adaptive dynamic programming algorithm is proposed for getting the approximate solution of the coupled Hamilton-Jacobi-Isaacs Equations (HJIE), and obtaining the Nash equilibrium strategy of mixed H2/H∞ control of nonlinear system.By adding the detection signal to the control strategy and the interference strategy, an approximate dynamic programming algorithm is acquired for solving mixed H2/H∞ control problems with unknown model without depending on model information of the system.Two critic neural networks and two executive neural networks are used to synchronously update two value functions, control strategies and interference strategies online.The unknown parameters of the neural network are estimated by generalized least squares.The simulation results verify the feasibility of the algorithm.

In view of the problem of low Signal Integrity Degree(SID)using the general method to construct the reconstructed matrix in the process of noise reduction in singular value decomposition, a new method is proposed by using cyclic matrix to construct the reconstructed matrix.The method can preserve the characteristics of the original signal information when constructing the reconstructed matrix by using the cyclic matrix.Then, the singular values of the cyclic matrix are decomposed, and the effective reconstruction order of the matrix is determined.Therefore, the purpose of noise reduction is achieved.Simulation results show that the proposed method has higher noise reduction accuracy and noise immunity than other methods, and the new method improves the practicability of the algorithm.

Maneuvering target tracking using the raw data with unknown threshold under low Signal-To-Noise Ratio (SNR) circumstance is a difficult problem.In this paper, an Interactive Multiple Model (IMM) Bernoulli Track-Before-Detect (TBD) algorithm is proposed.The algorithm uses the IMM method to predict the sampling particles in each target state of the filter, the Bernoulli filter for the recursion of the target particles, and the TBD algorithm in the particle updating phase, thus to realize the updating estimation of the existence probability and distribution density of the targets.In the particle prediction, several models are used to transfer the prediction, which makes the motion state of the predicted particles similar to that of the real targets.The method combines the features of the Bernoulli TBD algorithm with those of the IMM method, which can be used for the high-accuracy detection and tracking of maneuvering targets under the condition of low SNR.Simulation results show that the proposed filter can estimate the target position in real time, and has better filtering performance than the traditional Bernoulli TBD algorithm.

A 3D node deployment algorithm is proposed based on Improved Particle Swarm Optimization (PSO) algorithm for underwater sensor networks.By adjusting the weighting factor of the PSO algorithm linearly, the comprehensive deployment of the current deployment area can be realized while avoiding local optimization of the nodes.The oscillations near the optimal deployment position can be eliminated too.Compared with the virtual force algorithm, the proposed algorithm can achieve the optimal deployment effect with a shorter time, and effectively ensure the connectivity between the network nodes while obtaining a high 3Dcoverage rate.

According to the imaging features of dim targets, we put forward a target detection algorithm based on the local maximum mean of neighborhood and multi-scale morphological filtering.It is determined whether the image center is the maximum or not by the sliding window.If it is the maximum, the center pixel will be replaced by the maximum mean of the two directions of its four neighborhoods.Otherwise, the center will be assigned according to the calculated weighting coefficient by figuring out the two maximum gradients of four neighborhoods.It is implemented through the whole image for eliminating the noise and improving the signal-to-noise ratio of the original image.Then, multi-scale morphological filtering of the image is carried out and the background can be estimated effectively and be removed from the original image.After the threshold is calculated by using the improved adaptive segmentation method, the targets are extracted from candidate points.Multi-frame association is applied to sequential images for further reducing the false alarm rate.Experiments show that, the method is easy to implement, and can detect the whole target with high detection probability and low false alarm rate.

The infrared small targets in complex background are not easy to detect due to their fuzzy edges, and the false alarm rate is high.To solve the problems, an improved Top-Hat target detection method based on SUSAN background suppression is proposed.In this method, the background of the original image is suppressed by using SUSAN method, and then an opening operation is made to the suppressed image.Finally, the result of the opening operation is compared with the original image, and the result images are obtained by assigning values to them respectively.In order to verify the superiority of the improved Top-Hat method, the image after background suppression is processed respectively by using the traditional Top-Hat method and the improved Top-Hat method.The comparison results show that, the proposed algorithm can greatly improve the detection probability of infrared small targets in complex background, and effectively reduce the number of false targets, i.e., the false alarm rate.

Aiming at the limitation of single aircraft detection performance to missile attacking area, we studied the missile cooperative attacking area under dual-aircraft cooperative operation mode, and analyzed the guidance constraints under dual-aircraft cooperative attacking.Simulation was made for the missile cooperative attacking area of two kinds of aircraft formations.The simulation analysis shows that, the cooperative missile attacking area of the dual-aircraft cooperation is larger than that of the single aircraft, which is more beneficial to the attacking performance of the missile.

The flight control of the formation of multiple Unmanned Aerial Vehicles (UAVs) based on wireless network communication is easily affected by such factors as communication interruption and information collision.Based on a Token-Ring algorithm of distributed network, a method to switch communication topologies is proposed, and a concept of leader switching is introduced.The distributed control law is designed based on the consensus theory and the local relative state information, which is made up of two parts:tracking of the desired trajectory of formation and maintaining of the formation geometry.A double-integrator dynamics system model is used for simulation.The results show that:1) The proposed method can make the formation implement the desired trajectory tracking and maintain formation geometry in flight;and 2) The designed control system has strong robustness, which can keep the preset formation geometry even when some of the communication nodes fail.

To solve the problem of dynamic route planning for multi-rotor Unmanned Aerial Vehicle (UAV) formation, an improved hybrid algorithm combining ant colony algorithm with Rapidly-exploring Random Tree (RRT) algorithm was proposed.Firstly, the ant colony algorithm was used to search the original global route with the lowest cost, and the “cooperative avoidance-reconstruction” strategy was proposed in the local route planning.Then the improved RRT algorithm was used to modify the geometric route in real time, thus the UAV formation could avoid the static threats and unexpected obstacles and fly to the destination while satisfying the time constraints.The simulation results show that:1) The improved hybrid algorithm and strategy can implement the dynamic route planning for UAVs effectively;and 2） Compared with the common RRT algorithm, the optimality of the overall route and the online search rate of the local route are improved significantly.

Path planning of robot refers to the planning of an optimal collision-free path from the starting position to destination according to a certain optimization strategy.There are two suggested techniques covering all approaches in robot path planning:the traditional method and the heuristic method.This paper reviews the research status of different heuristic approaches in robot path planning and optimization, and then analyzes the performance and applicable scenarios of different algorithms.In addition, the latest technological progresses are also presented considering the superior quality of the artificial potential field method in the path planning.Finally, the advantages and disadvantages of various algorithms are analyzed, and it is proposed that the deep integration of the algorithms should be the future direction of the path planning technology.

In order to meet the high-precision requirements of a new fixed-aiming servo control system, the servo controller of the servo system is redesigned.The composition and working principle of the fixed-aiming servo system are introduced, and the mathematical model of each module of the system is established. The Auto-Disturbance Rejection Controller (ADRC) is applied to the system's speed loop, and the improved Nonlinear PID (NLPID) controller is applied to the current loop.The system is simulated by the S-Function module in the Matlab/Simulink simulation environment. The simulation results show that, the designed controller not only has high tracking accuracy, but also has good disturbance isolation performance, high adaptability and strong robustness, which provides a theoretical reference for the further study of high-precision fixed-aiming servo system.

The precise opto-mechanical analysis plays a key role in optimization design of the system.In actual conditions, the optical components of opto-mechanical system may have asymmetric changes due to the effect of coupled fields.To solve the problem, a 3D interface model based on Zernike polynomials fitting was built to improve the data transferring precision of opto-mechanical analysis.Thus the high-precision analysis under coupled fields was realized.To make an optimization design of a certain opto-mechanical system, we made an integrated analysis of the gravity field and the temperature field, extracted the asymmetric distrubution of optical surface changes, and made an analysis to the imaging quality of the system by using the 3D interface model.The results indicate that the interface model can be used in the actual condition of coupled fields for opto-mechanical analysis.

The sub-surface damage of the optical elements due to grinding and polishing may destroy the uniformity of the base material, result in the scattering of incident light, and seriously affect the optical properties of the product.It is very difficult to study the scattered signal due to the complex characteristics of the damage.The laser confocal microscopy testing based on the light scattering method is a fast and accurate sub-surface nondestructive testing method.It uses the sub-surface damage to the incident light scattering modulation signal to analyze the sub-surface damage information of the optical component.Aiming at the scattering characteristics of the damage, the Finite Difference Time Domain (FDTD) method is used to establish the electromagnetic simulation model for the special damage of particles and microcracks.The scattering field distribution of the incident light is studied, and the curve of the light intensity is detected at different depths.The damage light intensity detection curve can reflect the information of the size and depth of the particles and the width and depth of the microcracks.The results of the study have important theoretical significance for the study on nondestructive detection of sub-surface damage of optical elements.

Aiming at the problem that the Gaussian Mixture Cardinality Balanced Multi-Target Multi-Bernoulli (GM-CBMeMBer) filters are limited to the fixed birth position and cannot provide track information, a labeled GM-CBMeMBer filter with adaptive one-step track initiation is proposed, which makes full use of the Doppler information of the airborne Doppler radar.In the predicting step, the proposed algorithm provides track information by introducing track label.After selecting the measurements that may correspond to the newborn targets, the position estimation and velocity estimation of newborn targets are calculated by using the converted position measurements and Doppler measurements respectively.In the updating step, the target states are updated sequentially by using Doppler measurements after they are updated with position measurements.The results of simulation show that the proposed algorithm performs well in track initiation and can effectively provide track information.

The threats of anti-ship missiles to the surface warships are analyzed at first. To improve the air-defense and anti-missile capability of the whole warship formation, the concept of relay guidance is introduced and its significance is given. Then the switching mode, the basic process and the main tasks of the shifting platform of the relay guidance are analyzed in detail. Finally, the critical technologies and challenges in the relay guidance are pointed out, which provides a direction for future research.

Bayesian sequential test and Bayesian recursive estimation method can improve the traditional test evaluation method respectively from the aspect of hypothesis testing and parameter estimation.The two methods are used together here and applied to evaluation test of missile hit accuracy, which can combine test with estimation closely.It can make full use of priori information to make up for the lack of field data, and formulate a reasonable and effective evaluation scheme, which makes the test results more accurate and uses less ammunition for experiment.The example analysis shows that this method can effectively improve the test and estimation result, and is suitable for the evaluation test under the condition of small sample.

The fault diagnosis of gas path system in integral bipropellant propulsion is investigated. Aiming at the problems that the failure rate of gas path system is relatively high and some key information can't be obtained through the sensors, a method of building Modified State Class Graph (MSCG) based on Partially Observed Time Petri Nets (POTPN) and State Class Graph (SCG) is presented. Firstly, the transitions are divided into observable and unobservable transitions according to the observability of the actuators, and the time intervals are modified based on the different relationships of the transitions (synchronous and asynchronous).The MSCG is then built with time Petri nets.Based on the proposed fault diagnosis method, all the effective paths that satisfy the observable transition triggering time and sequence information are found out, and it is determined whether the effective paths have fault transitions.Finally, taking the gas path system in integral bipropellant propulsion as an example, and based on the observability of the actuators, a Petri net is built for making fault diagnosis to the unobservable part of the system, which verifies the effectiveness of the algorithm.

A non-linear error algorithm is proposed to achieve higher pointing accuracy for star sensors under carrier movement.The error sources of the star sensors are analyzed, and a linear error model of the measured vectors is established.Based on operating features of the star sensors and the sources of the nonlinear error, an improved nonlinear error algorithm is derived to eliminate all the pointing errors.An experiment is made taking a certain type of star sensor as an example.The experimental result shows that the algorithm can identify the errors more accurately and improve the performance of the star sensors.

A simple PID controller and a dynamic PID controller were designed based on the dynamic modeling of the quadrotors, and the fuzzy rules were established for the dynamic adjustment PID, which could implement the attitude control of the quadrotor.Simulation was made to the two kinds of PID controllers.The results show that, compared with the simple PID controller, the dynamic PID controller has better control effect.