For Avionics Full Duplex Switched Ethernet (AFDX) networks with a large number of Virtual Links (VLs), the availability of configuration and the efficiency of simulation implementation should be taken into consideration, especially for traffic policing mechanism. The AFDX network simulation model that contains preprocessing and postprocessing operation is developed on the OPNET simulation platform. It can ensure the operating efficiency while completely simulating the internal traffic policing mechanism of the exchanger. By preprocessing the configuration file, the model solves the problem of disposable loading mass VL configuration data. A token leak bucket algorithm with large scale VL is implemented in the traffic control module. Through the designed experiment, it is proved that the AFDX network simulation model has the ability of processing large-scale VL, and the traffic control module has high effectiveness and efficiency.

The teaching recording and broadcasting system based on image recognition technology usually requires the close-up of the indoor students from the camera by automatic identification and position. A head detection algorithm based on multi-feature fusion for the indoor students is proposed to solve this problem. Firstly, head candidate regions are extracted through setting a threshold value based on the color characteristics of human hair. Then the head region of all the students can be detected by shape features of the hair region and skin color features of the face region. Finally, the speaking student can be captured by detecting the position change of the center of the contour in the vertical direction of the image when he stands up. The method was used for image processing of several angles of classroom video, and the experiment results show the effectiveness of it in detecting the head region of students.

Aiming at the Track-Before-Detect (TBD) problem of near space hypersonic target, a kind of track-before-detect algorithm based on Random Hough Transform (RHT) is proposed. By making error analysis to target measurement data, the time-radial distance plane random Hough transform is used to convert measurement to the parameter space. And the selection criterion of parameter space permissible error is obtained by calculation and analysis. Then the target measurement can be accumulated effectively. The algorithm validity is verified by simulation, and the algorithm performance is compared with the algorithm based on Standard Hough Transform (SHT). The simulation results show that, compared with the standard Hough transform, the algorithm in this paper can effectively reduce the algorithm running time and the false track number, and realize effective detection of near space hypersonic target.

The path planning for warship-aircraft joint operation is studied. Firstly, the weapon system of the destroyer is analyzed to obtain the safe distance when the shipboard helicopter and the destroyer are performing a task cooperatively. Since the traditional A* algorithm cannot be applied directly to the path planning for warship-aircraft joint operation, the security costs and the path safety factor are introduced. An improved weighted A* algorithm is given based on the traditional algorithm, to solve the path planning problem for warship-aircraft joint operation. Finally, a case simulation is given to verify the effectiveness of the improved algorithm.

The path planning for warshipaircraft joint operation is studied.Firstlythe weapon system of the destroyer is analyzed to obtain the safe distance when the shipboard helicopter and the destroyer are performing a task cooperatively.Since the traditional A* algorithm cannot be applied directly to the path planning for warshipaircraft joint operationthe security costs and the path safety factor are introduced.An improved weighted A* algorithm is given based on the traditional algorithmto solve the path planning problem for warshipaircraft joint operation.Finallya case simulation is given to verify the effectiveness of the improved algorithm.

A novel direct adaptive fuzzy backstepping control approach is presented for a class of output error constrained nonlinear system with input saturation feature. A Butterworth low pass filter and a fuzzy state observer are designed to estimate the unmeasured states of the system which control directions are unknown. To address the output error constraint, a barrier Lyapunov function is employed. Then the smoothness properties of a hyperbolic tangent function and a Nussbaum gain function are used to handle the input saturation. A robust controller is designed combining the backstepping approach with the dynamic surface method. It is proved with the Lyapunov analysis that the proposed control scheme can guarantee that all the signals of the closed-loop system are Semi-Globally Uniformly and Ultimately Bounded (SGUUB). Simulation is made by taking the longitudinal dynamics with parameter uncertainty and external disturbances as the model. The simulation results show that the output error is limited in the constrained range, and the proposed control approach has strong robustness.

The bullet holes detection using image difference technology has the problems of over-detection, leak-detection, being sensitive to noise interference and harsh request for imaging condition. A bullet hole object detection method based on wavelet transform using fusion rules was proposed to overcome the limitations. In the wavelet domain, different fusion rules were applied to the low-frequency and the high-frequency sub-images to revise the wavelet transform coefficients, for increasing the object coefficients while decreasing or resetting the non-object coefficients. Then, it used the maximum points to the low-frequency coefficient and reduced the noise of high-frequency coefficients. The final bullet holes images were obtained through invert wavelet transform. Experimental results show that : the method can overcome the shortcomings of the image difference method, obtain images of bullet holes with clear edge, and improve the veracity and precision of the bullet holes detection.

For the autonomous flight of Small Unmanned Aerial Vehicle (SUAV) without GPS, a fast Simultaneous Location and Mapping (FastSLAM) based on Improved Particle Swarm Optimization algorithm (IPSO), i.e., IPSO FastSLAM, is presented.An adaptive resampling method is introduced into the proposed algorithm to effectively overcome the degradation of particles and reduce calculation burden on frequency resampling.But resampling process may cause sample depletion, thus diversity measure of particle sets is put forward as an inspiration factor, leading the particles optimization search process after resampling, to ensure diversity particle set optimal.Finally, simulation research is carried out by using the proposed algorithm on SUAV, and result shows that this method can get better performance on estimation accuracy and feasibility.

The sea surface targets are densely located and have diverse types, and the large amount of clutter false alarm points may cause high error association rate in tracking processing. In order to solve this problem, a sea surface targets association algorithm based on speed partition and multiple information utilization is proposed. First, the targets are divided into three categories according to their speed, respectively corresponding to different speed ranges. In each speed range, the corresponding range gate, speed gate and association rules are set up, where different association rules are adopted based on the feature information of targets, such as shape, size, amplitude and compact degree, etc. Then, the sea surface target track is filtered. The processing results of collected data show that the algorithm can obtain good tracking effect.

To the issue of the adaptability of a single reference image under the condition of multi-aircraftcondition of cooperative terminal guidance, an effective method of reference image adaptability evaluation was presented. The model of multi-aircraft cooperative guidance was established, with focus on analyzing the relationship between detection angle and initial aircraft position. A method for analyzing the adaptability of reference image was proposed based on actual parameters and the model of detection angle. Geometric distortion was applied to the real-time images, and the threshold angle was obtained through a lot of scene matching simulation experiment by using the normalized product correlation algorithm. Simulation verified the feasibility of the method, which provided a theoretical basis for real-time image correction, reference image reformation and adaptive algorithm improvement.

The fly-wing UAVs have large individual difference, a large number of control surfaces, short longitudinal control lever and static instable heading. To solve the problems, this paper presents a direct allocation method from angular acceleration to the control surface, and a control law taking angular acceleration as the control instruction. First of all, the angular acceleration is directly allocated to the control surfaces that have been graded in discrete state. Taking the angular acceleration as control instruction, a longitudinal Robustness Servomechanism Linear Quadratic Regulator (RSLQR) control law, and a lateral stabilization control law, are designed. The simulation results for the sample UAV under nonlinear condition show that: 1) The angular acceleration allocated to the control surface satisfies the distributed precision requirement; and 2) The control law with the angular acceleration as control instruction has high tracking accuracy and satisfies the speed requirement.

The traditional track-before-detect algorithms based on non-coherent integration demand high SNR for each single frame data, and the effective time for signal integration is short. In this paper, a novel and efficient track-before-detect algorithm is proposed based on the particle filter with coherent integration. The target states are estimated by the samples of the delay, velocity, and power information of target. Then, the matched filters are redesigned according to the target delay, and the echoes are filtered again to compensate for their delay. The simulation results show that: at the low SNR of -5 dB, the algorithm still has fine tracking and signal detection performances by extending time for signal integration.

A refined track initiation algorithm is proposed for the objects in dense formation.The measurement clustering algorithmwhich needs significant amount of computationis not needed in the method.Firstall possible associate point sequences are built up by extending the track initiation conditions.Thenclustering is made to all the sequences by comparing the different sequences to see if they have the common measurements.At lastoptimized distribution is taken to the initial relative sequences belong to the same clusterand the optimum scheme is selected to each object in the formation for track initiation.Simulation results prove that the method has fine performance on formation track initiationlow computational burden and high accuracy rate on track initiation.

The current threat evaluation methods need to determine the weights of all evaluating indexes, which depends greatly on experts experience. To solve the problems, a catastrophe decision-making method is proposed for target threat evaluation. The method explores the influence factors of the threat degree, and a multi-layer evaluation index system is built up based on the primary and secondary relations of all factors. Then, primary catastrophe patterns of all sub-layer indexes and its upper layer indexes are established based on catastrophe theory, and catastrophe membership function value of sub-layer indexes are calculated using the normalization formulae, to describe the influence degree of sub-layer index to upper layer index. Then, catastrophe membership function value of upper layer indexes are calculated based on catastrophe decision-making principles. Finally, the total catastrophe membership function value of top index is calculated out, and the result is used for threat degree sequencing and decision-making. The method has rigorous theoretical foundation, concise and efficient calculating progress, and it is unnecessary to compute the weights of all indexes. The feasibility and effectiveness of the method is verified by the result of an actual calculating example.

The positioning method of TDOA (Time Differences of Arrival) is applied to the positioning of aircraft in deck landing.Several major kinds of TDOA algorithms are analyzedand the Spherical Intersection (SX) algorithm is chosen based on the practical situation and the limits of shipboard aircraft landing.Considering that SX algorithm has large computation burdenthe equation coefficient matrix may be illconditioned and so onwe propose an algorithm based on linearization equation.By adding a range difference equation on the foundation of SX algorithmthe nonlinear equation is transformed into a linear equation.The simulation results indicate that : compared with SX algorithmthis algorithm has higher accuracy and smaller computation burden.

Integrated Modular Avionics (IMA) system may load different kinds of software to a general hardware resource platform for realizing different functions, which brings about a high requirement to reconfiguration of the software components. The existing certification technology is unable to evaluate the safety of the reusable software components. In this paper, the certification requirements of the reusable software components are analyzed, and the validation elements and the evaluation requirements are given. This research can provide a theoretical support for the airworthiness certification of reusable software components.

In camera parameter calculation, many distortion models ignore the effect of Center of Distortion (COD) and take the principal point or the center of the image as COD. In order to improve the precision of calibration result, the COD is introduced to the distortion model and added to the intrinsic parameters. To compensate for the problems of large computation burden and low efficiency due to the added parameter, Stochastic Parallel Gradient Descent (SPGD) is introduced to optimize the result. Results of digital simulation and experiments show that the SPGD based multi-parameter camera calibration method has high precision, fine robustness and can converge rapidly.

Focusing on the localization problem of indoor mobile robots, a credibility based adaptive federated filter localization method is designed. Firstly, considering the features of mobile robots and the indoor environment, a localization system with multiple sensors is designed, and the sensors are configured accordingly. To handle the information from multiple sensors, a federated filter is introduced, and each sub-filter is designed. On the basis of it, data fusion is made to the measured data for obtaining the pose estimation of mobile robots. Then, considering the characteristics of a particular sensor, the credibility factors of its measured data are given by using fuzzy reasoning. Meanwhile, based on the credibility factors, an adaptive fusing algorithm of the federated filter is designed, and the localization result of indoor mobile robots is given. Finally, simulation results are given to verify the effectiveness of the designed localization algorithm.

Based on the two-axis semi-strapdown stabilized platform, how to realize the functions of disturbance rejecting and stable tracking was researched. Analysis was made to the stabilized platform and the model was established. The reason for selecting Auto-Disturbance Rejection Control (ADRC) method was analyzed by comprehensively considering the factors of control requirements, controlled object characteristics and control technical state, and the advantages of ADRC were given. The controller was designed with four modules as tracking differentiator, extended state observer, nonlinear state error feedback control law, and disturbance estimation and compensation. The result of parameter adjusting was also presented. Simulation verified the effectiveness of the controller designed by comparing it with traditional PID. Step response verified the effect of disturbance rejection. Through inputting sine signal, the effect of stable tracking was tested. The method of Monte Carlo verified the robustness of the control system when the model parameters of controlled object fluctuated around the reference value by 20%. Simulation results show that: 1) The effect of disturbance rejection is obviously better than that of the traditional PID;and 2) The tracking error of this controller is only 50% of the PID, while the robustness doubled.

Remaining Useful Lifetime (RUL) estimation is a significant part of health management. A RUL estimation method is proposed by combining the lifetime data with the degradation data based on diffusion process, and the RUL distribution is derived with the concept of the first passage time. In addition, the parameters are optimized offline and updated online. Firstly, maximum likelihood parameter estimation value based on the lifetime data is considered as the initial value of Bayesian updating. Secondly, the lifetime data and the degradation data are combined by Bayesian method to update parameters of the degradation model. Finally, the real time estimation of RUL is realized. The experimental results verify the effectiveness and superiority of the proposed method.

When quad-rotor aircraft is trapped in the great disturbance of wind, windup phenomenon may appear for simple PID controller, under the combined action of integration element and saturation limit element. Thus may lead to deterioration of system's dynamic responses, and big overshoot or imbalance of quad-rotor. A dynamics simulation model is established for the quad-rotor aircraft, and the causes of windup phenomenon are analyzed. An anti-windup PID controller with fuzzy variable parameters is designed to alleviate the windup phenomenon. Contrastive analysis is made to the controller with the existing fuzzy PID controller and the anti-windup PID controller with constant parameters. The results of simulation indicate that, the fuzzy PID controller based on anti-windup technology can effectively restrain the windup phenomenon, and speed up the attitude adjustment process of quad-rotor.

Considering the function requirement of hardware-in-the-loop simulation control platform for a certain guided weapon, we put forward a system design idea based on VMIC real-time network and Ethernet. The design scheme and realization approaches are introduced. A real-time Automatic Test System (ATS) is developed by using RTX subsystem together with LabWindows/CVI. By the use of integrated hardware design and modularized software design, the control platform can implement such functions as real-time video signal acquisition to the seeker, data recording and processing, real-time flight data curve displaying, real-time monitoring and status indication, video playback, and fault diagnosis and treatment. The control platform has the characteristics of fine real-time performance, universality and expansibility, which can support the hardware-in-loop simulation effectively and provide a technical support for weapon system development and test.