Based on the understanding to regional search features, a viewpoint is put forward that buoy array deploying, buoy array monitoring and their relationship should be taken into integrated consideration for anti-submarine patrol aircraft to search submarine by using sonobuoy.Further more, two types, totally three kinds of methods are put forward for the submarine search based on the analysis to sonobuoy regional search situation, and the action methods after contacting are given.The concept of standard buoy array is put forward corresponding to each search method, and search efficiency calculation models are established.The planning steps of submarine regional search for anti-submarine patrol aircraft are also given.The two methods of the first type of search method, synchronous search of deploying and monitoring, are mainly discussed, and the examples of regional search using the two methods are given.

In order to combine the advantages of global threshold with local threshold method, a double-threshold binarization method based on image enhancement was proposed. The two thresholds were calculated out by using OTSU and Kittler method, and preprocessing was made to the points with gray value greater than the upper threshold or less than the lower threshold. Sauvola method was used to judge the points with gray value between the two thresholds. Double-threshold remained more detailed information with less time cost, but still had the problem of uneven illumination. Therefore, a new image enhancement algorithm was proposed. The image was divided into four areas equally, and the differences of the average grey value of the whole image with that of each area were taken. Then by using the four weights related to pixel points'location, the corresponding gray value on each point was compensated. Image enhancement was made repeatedly until the average gray value of the four areas was controlled within a certain range. The binarization of uneven illumination image was improved greatly after this image enhancement.

Aiming at the multi-sensor management problem in target recognition stage under complex aerial defense combat environment, a new multi-sensor scheduling method is proposed based on Rényi divergence.Firstly, the D-S evidence theory is applied to obtain the Rényi divergence of different sensors matched with different targets.Then, the sensor allocation model based on the maximized total Rényi divergence is established.Besides, the Quantum Particle Swarm Optimization (QPSO) algorithm is improved in order to quickly solve the management model.Finally, the experiments show that the improved algorithm is feasible and effective.

Visual navigation method is an effective method for the autonomous landing of Unmanned Aerial Vehicle (UAV).This paper designs a landmark that consists of a ring and a circle made up of three primary colours, and a method for estimating the pose and position of UAVs based on the landmark is presented.The method first determines the target area through the detection of the outer ring, and then estimates the position and attitude parameters of the UAV relative to the platform according to the boundary lines of the internal tricolor circle and different color regions.Simulation experiments are conducted to the UAV at different heights.The results clearly show that the method can accurately determine the position and pose parameters of UAV relative to the landing pad, and can meet the requirement of real-time position and pose parameters measurement when UAV is landing.

In order to improve the effect and speed of Unmanned Aerial Vehicle (UAV) reconnaissance video registration, a fast registration method based on scene matching is proposed.Firstly, a feature matching algorithm based on AGAST-Difference and Fast Retina Keypoint (FREAK) is proposed to match the video frames.Then, the matching region search method is proposed to find the matching region for the target frame in the satellite digital map.Finally, the video frame is registered to matching regions, and the homography matrix is calculated out according to 2D relationship of the matching regions for implementing the splicing.The experimental results show that:1) The feature matching algorithm based on AGAST-Difference and FREAK has great advantages in scale, rotation, viewpoint and so on;and 2) The matching region search method can avoid the error caused by the Position and Orientation System (POS) and the introduction of control points, thus the correction accuracy and speed are improved.With the splicing speed up to 25 frames per second for videos of 810×612 resolution, the 2D localization accuracy of our algorithm for a ground target can reach 7.87 m when the UAV flies at about 1000 m above ground.

In processing high-resolution remote sensing images, the SIFT algorithm has large calculation burden and great amount of time cost.To solve the problems, we made improvement to the SIFT algorithm on extreme point detecting and similarity measurement.Firstly, the improved algorithm uses the 14 points that are closer to the detecting point and have higher weight instead of the 26 points of the SIFT algorithm to detect the extreme points, which can reduce calculation amount for extreme point detection.Secondly, in the similarity measurement of SIFT feature vector matching, the linear combination of Manhattan distance with Chebyshev distance is used instead of Euclidean distance, which is more simple and can decrease the computation complexity and improve the efficiency of matching.Finally, simulation results prove the effectiveness of the algorithm by using the measured remote sensing data.

Improvements are made to ViBe (Visual Background extractor) algorithm for enhancing its test effect and test speed.The algorithm utilizes several pixel values from consecutive frames to train and construct the final samples of background during initialization, thus to decrease the ghosts effects on precision in detecting an object and partially remove the noises on the edge of background objects.In the process of pixel matching, a classified threshold and a match threshold for scene complexity of the pixel are adjusted dynamically to adapt complicated background scenes and diminish the disturbances of incorrect foreground pixels.In order to reinforce the robustness of the improved algorithm, an adaptive time-subsampling factor is utilized to accelerate elimination of the ghost caused by the departure of background objects and recovery of the background samples.Experiments show that the algorithm presented here can remove the ghost and noises effectively and is appropriate for complicated background scenes detections.

In mission planning of UCAV formation, the flight route optimization is an important research topic. The optimum flight route of UCAV based on uncertain linguistic preference information is studied. First, the indicators for evaluating the UCAV route are presented, and the definition of uncertain linguistic decision matrix is described. Then, analysis is made to the expected possibility and mathematical expectation of each index corresponding to the flight route, and the group decision-making optimum flight route analysis method based on uncertain linguistic preference information is given. Finally, a numerical example is given to illustrate the usage of the proposed approach.

In target tracking system, the measurements from different sensors might arrive at the fusion center out of sequence because of the different communication delays, and thus result in the Out-of-Sequence Measurement (OOSM) problem.Usually there are multiple OOSMs in the actual working process of the system.Aiming at this problem, the common situation is classified, and Dl algorithm is proposed within the forward prediction filtering framework.The algorithm can update the state estimation and the covariance matrix on each moment of OOSM fusion period, and deal with multiple OOSMs with arbitrary steps of delay.In addition, the equivalent measurement information filter is deduced for single OOSM without requiring the inverse of the state transition matrix and the discrete model of process noise.Simulations verify the precision and effectiveness of the proposed algorithm.

A novel parallel graph-based image segmentation algorithm was constructed to segment high-resolution image precisely in real time.This algorithm adopts parallel structure and divides the image into multiple regions.Parallel processing can be made to the non-adjacent regions.This algorithm can be deployed easily on multi-core processors for multi-core parallel processing to shorten the runtime.In order to segment precisely and enhance the ability in clutter scenes, this algorithm combines the smooth regions directly by setting low weight threshold.Based on this method, the object regions can be segmented coherently. Experiments demonstrate that this algorithm can segment high-resolution images rapidly and precisely, has better performance than the traditional segmentation algorithms, and can achieve high level performance in segmenting images with complex background.

The application of mid-infrared laser of Directed Infrared Countermeasures (DIRCM) system in foreign countries is introduced.Based on the requirements of DIRCM system for mid-infrared laser on such indexes of laser power, beam quality, wavelength, working temperature, volume and weight, the key technologies of different types of mid-infrared lasers used in airborne DIRCM system are analyzed.The development tendency of mid-infrared laser used in airborne DIRCM system is presented in the end.

Remote Data Concentrator (RDC) is used to collect the distributed digital signals over the aircraft to the core processing machine.First of all, a solution is put forward to achieve the transformation between ARINC 429 bus data and AFDX network data through HI-3593 chip.HI-3593 has the SPI bus interface to facilitate with the FPGA chip integration.Based on this, the HI-3593 is combined with controller IP core of Ethernet MAC layer, Verilog is used to implement receive-send of SPI protocol and AFDX framing logic development, and eventually to achieve data centralization and conversion.Subsequently, the access to Synchronization Client (SC) in AFDX is proposed, which can achieve synchronization according to the received Protocol Control Frame (PCF), so that RDC can access to the Time Triggered Ethernet (TTE) with the prerequisite of complete compatibility with AFDX.

The traditional angle-fixed fuze has low initiating controlling accuracy when intercepting an object moving at high speed, such as a Tactical Ballistic Missile(TBM).Therefore, we proposed a new algorithm of adaptive control based on phased array fuze.The planar phased array technology was introduced in the algorithm to implement adaptive target tracking.On this basis, a new model of the optimum detonating angle was established.An adaptive initiating delay time was used to prevent explosion in advance because of beam stepping and realize intelligent coordination.Simulation indicates that this method can realize effective control of the optimum point of burst, and improve the kill efficiency to the target.

A hybrid task scheduling method is presented, in which strict periodicity criteria is adopted to certain important or easy-to-schedule tasks, while the rest is scheduled based on the jitter minimization criteria to mitigate the variance of intervals between any two adjacent jobs of a given task. To develop this method, a measure for strict periodicity schedulability, and a feasible slot selection scheme for variable-length jobs are proposed. The min-plus algebra is used for making multiplication of weighted transferring matrix, thus to implement slot allocation with minimum jitter of current task. Case study shows that: Compared with the control groups only based on minimum jitter scheduling, our hybrid method can gain increased proportion of strictly periodic tasks and the scheduling scheme obtained has smaller jitter rate in the worst case.

An improved method for path planning of robots is proposed for use in complex and dynamic environment with randomly moving obstacles.In order to avoid obstacle safely without too much circuities, a new rule is used for avoiding randomly moving obstacles with consideration of the relative position and velocity between the robot and obstacles.To the object moving with uniformly variable speed, an improved artificial potential method is adopted with consideration of the relative velocity and acceleration, which can help the robot to keep pace with the object.The simulation results based on Matlab platform show the effectiveness of the algorithm.

In order to detect the damage locations of the cantilever beam with multiple damages, modal analysis based on the large commercial finite element software ABAQUS and modal experiment test method were adopted by using modal strain energy method. The low-order modal strain energy before and after damage of a cantilever beam structure was obtained, and the strain energy difference was used as damage index to identify the damage. The simulation and experimental results showed that the modal strain energy can be used to locate the damages of the cantilever beam. Based on the validation of the effectiveness of the method, the influencing factors of the beam structure damage detection were analyzed, including the arrangement of measuring points, the number of sensors, the position of sensors and the number of modal order. The result demonstrated that: 1) The damage location of the beam with multiple damages can be detected by the first three order of modals, and the locating effect is the ideal when the distance between the measuring points is roughly equal to the width of the beam;and 2) The number of sensors has no obvious effect on the damage detection and localization.

Analog signal is one of the key data types of flight control computer.We designed a kind of A/D conversion unit with high speed, high precision and strong inhibiting ability to the noise and electromagnetic interference.To suppress and eliminate the noise interference and improve the stability of the A/D sampling data, we used the differential signal acquisition circuit, combining with the hardware and software design of the filter.The test results showed that:under the condition of typical interference, the high precision A/D units resolution of data acquisition reaches 15 bit and the accuracy is 14 bit.Compared with the original example of flight control computer, the A/D data acquisition precision is increased by 2~3 bits and flight control computer works stably, which meets the requirements of UAV flight control computer analog data acquisition.

Aiming at the demand of monitoring deep coupling system errors, this paper presents a method based on Principal Component Analysis (PCA) for the error monitoring according to the statistical characteristics of view measurement of deep coupling system.The normal observation data is used to construct the PCA model, and the parameters of the model is used for monitoring the observed data in the deep coupling system in real time.This method is used to detect and mitigate the errors in the deep coupling system, while the wavelet denoising is adopted to improve the performance of error detection.Finally, the result of simulation verifies the feasibility and effectiveness of the method.

According to the mission of Helmet Mounted Sight/Display System (HMSDS), an effectiveness evaluation index system was established.Based on ADC model and the characteristics of cloud model to fuzzy problem evaluation, and by calculation of the capacity matrix C, the cloud model algorithm was introduced when calculating the cloud membership value of each index.Thus the cloud membership degree of the system effectiveness was obtained.Finally, analysis was made to the cloud membership degree through simulation, and the influence of cloud droplet distribution on the result of evaluation was given.

In order to improve the mission completion capability of Line Replaceable Unit (LRU) system, and reduce the maintenance resource consumption, a maintenance decision method for multi-state system based on Non-Homogeneous Continuous Time Markov Model(NHCTMM) was provided.NHCTMM was used to describe the degradation process of components, and the universal generating function was used to analyze the reliability of the system.Based upon the imperfect maintenance decision model, an imperfect preventive maintenance decision method was proposed, which ensured that the system could obtain maximum benefit-cost ratio in the limited service period.Verification was conducted to a radar power amplifier LRU system, and the result showed that this method has a strong versatility and engineering application value.