In order to solve the problem of high Constant False Alarm Rate (CFAR) in single frame detection of radar clutter, a scan-to-scan accumulation algorithm based on velocity template is proposed in this paper.Firstly, velocity templates of different velocities and accelerations are constructed based on the movement characteristics of the targets, covering all the possible target trajectories.Secondly, the velocity templates are used to match different moving targets for making binary accumulation and detection judgment.During the accumulation, Doppler velocity information is used for assistant judgment, thus can further reduce the influence of the false alarms to detection performance.Finally, simulation results show that this algorithm can effectively suppress the radar clutter.

To deal with the problems of the increased calculation complexity and decreased real-time performance due to the introduction of the fading factor in Strong Tracking Cubature Kalman Filter (STCKF) algorithm, a simplified STCKF algorithm is proposed.By proving that the time update of STCKF algorithm is consistent with one-step prediction process of Kalman Filter (KF) algorithm, the simplified STCKF algorithm is derived and the complexity of the algorithm is analyzed.The simulation results show that the simplified STCKF algorithm can effectively improve the real-time performance of the algorithm while keeping the filtering accuracy.

To build up the system model in aircraft maintenance simulation, a system modeling method is proposed based on extended reachability matrix together with component design of AGENT. It can not only solve the problem of the expression of logic relationship among the LRUs, but also can provide the system with redundancy. The method can describe the component's work logic in the system and the effect of component state change on the system. The logic of aircraft system can be abstracted and transformed into the effable object of computer with this method. Through the analysis of the reachability matrix, the component related to the behavior of the signal transmission and the behavior of the service can be defined. At last, the feasibility of the method is verified by constructing a logic function model of Automatic Flight System (AFS).

Considering the deficiency of signal interception in Electronic Support Measure (ESM), a new method was proposed under the reverse thinking of taking the characteristics of targets as the primary index.First, the known intelligence from different sources is fused via Beta distribution, and then the probability distribution of the next moment is estimated by using the instrument of Bayesian theory.Based on the probability distribution, a resource scheduling method is proposed by using the theory of optimal search and Shannon entropy.Finally, the simulation results proves the effectiveness of this method according to three indexes as the total number of interception, the remained uncertainty of task domain and intercept time used.

Aiming at the path planning for the Unmanned Aerial Vehicles (UAVs) in flight mission, a novel improved Artificial Bee Colony (ABC) algorithm is presented and used in flight mission.The path planning problem is transformed into function optimization based on this algorithm.The algorithm can evolve toward a better direction with the information exchanges among the colony and mechanism for the survival of the fittest.In the stage of employed bee search, an adaptive search strategy is adopted to increase the speed of convergence.In the stage of following bee search, a new probability of selection strategy is introduced to keep the diversity of the population.And in the stage of scout bee search, the chaotic search operator is used to improve the ability of global search.Through the standard function tests and simulation of path planning, the superiority of the improved algorithm is proved.All the results show that the proposed algorithm can improve the global optimizing ability, has great advantages on convergence speed and robustness over the traditional ABC algorithm, and is fit for UAV path planning.

The accuracy of the traditional ω-k algorithm of Frequency Modulated Continuous Wave (FMCW) Circular Synthetic Aperture Radar (CSAR) for image interpolation when reconstructing the cylinder areas has direct influence on the quality of imaging, and the process needs a large amount of calculation.To solve the problem, an ω-k algorithm based on Nonuniform Fast Fourier Transformation (NUFFT) is proposed, by which the echo signal of wave-number domain is deduced according to the fourth order Taylor expansion based on the slant range from radar to target.On the basis of which, the two-dimensional NUFFT is used instead of the interpolation function, and implements focused imaging.

Conventional tracking methods describe the target with a bounding box.As the bounding box is likely to contain some background regions and will degrade the tracking performance, a superpixel tracking method via online multiple instance learning is proposed.In training stage, input frame is segmented into superpixels, which are divided into several instance bags with clear labels according to their location.The tracking is thus converted into a multiple instance learning problem.Then, online multiple instance learning is implemented with the algorithm.The maximum of instance bags log-likelihood function is calculated to get K best weak classifiers, which are combined into a strong classifier.In detection stage, a confidence map is generated by the strong classifier in the subsequent frame.Finally, the state of the tracking target is estimated with the confidence map in particle filter framework.The proposed method runs at a rate of 15 frames per second on a laptop.Extensive experimental results on challenging sequences show that the proposed method performs well in terms of robustness and accuracy, especially for the target under complex background, moving at high-speed or is occluded.Compared with the original superpixel tracking, the typical values of precision and success rate of the proposed method are increased by 21% and 26%, reaching 91% and 90%, respectively.

Considering the optimization of such indexes as convergence and coupling degree in service identification algorithm, we proposed a service identification algorithm based on Weighed Network Optimized Clustering (WNOC) by using the relational degree model and the method of network topology clustering, introducing the adjacency parameter of clustering, and taking the coupling-convergence degree as the optimized objective function. Simulation was made with Matlab to a certain example, and the optimal clustering result was selected according to the coupling-convergence degree optimized model. The result proves the validity of the method in service identification.

vilian GPS has found wide applications in civilian areas, while spoofing may lead to malfunctioning of it. Spoofing is a serious threat to civil GNSS system, and therefore it's necessary to study how to detect and reject the spoofing signals. Firstly, an anti-spoofing approach to reject undesired signals by using null-steering is presented. Detailed discussion is given to the method's procedure and performance. Then the suppression of spoofing signals and noise signal is studied, and a method to optimize the weight vectors is proposed. Simulation results show that the optimization significantly increases the attenuation of undesired signals. As C/N0 increases, the attenuation approaches -60 dB (which is only -30 dB without optimization). Therefore, the spoofing signal is restrict to enter into the array. Finally, analysis is made to the impact of null-steering on visibility of GPS satellites. The results show that if the satellite is usable when the SNR is reduced by 12 dB, then all the satellite will not be affected.

For the feature point matching of SAR images used in navigation system, a feature point extraction approach is proposed based on Facet model.Firstly, the image intensity surface is well fitted through the Facet model.Then the second-order directional derivative of the center point of the fitting surface is calculated out, and the point whose second-order directional derivative is less than zero is taken as the potential feature point.Through normalization of absolute values for maximum values of the potential feature points and local non-maxima suppression, the feature points are obtained.Experimental results show that the proposed algorithm can successfully detect the feature point, and the real-time performance of the algorithm is better than that of the traditional SIFT algorithm.

The cost function of cooperative multi-task assignment for multiple UAVs is studied.The two main objective functions for the multi-task assignment are minimum cumulative distance travelled by all the UAVs to perform the required tasks and minimum time for the UAV team to accomplish all the required tasks.Both of them have their own limits, and there are conflicts between them.On this basis, a weighted sum method is employed, and a new cost function that combining the above two performance criterions is established.By choosing different weight values, the intention of the operator can be reflected.The discrete particle swarm optimization algorithm is applied to solve the cooperative multi-task assignment problem.Simulation results demonstrated the feasibility of the proposed cost function and algorithm.

Aiming at the problem that conventional airspace search method has a low effectiveness in radar EW reconnaissance, a dwell time adjusting method based on the minimum description length criterion (MDL-ADT) is proposed.The Digital Beam-Forming (DBF) technology is introduced in airspace search, and the relationship between the intercept probability of radar reconnaissance receiver and the beam dwell time is analyzed.The method has two steps:1) Pre-searching, using the MDL criterion to estimate the source quantity in each beam;and 2) Allocating the dwell time according to the distribution of signal sources in airspace, and implementing airspace search.The method ensures most efficient utilization of the resources of EW reconnaissance system by reasonable distributing of the dwell time.Finally, a simulation example shows that the proposed method can improve the airspace searching effectiveness by 20%.

This paper reviews some main results and progresses in consensus-based formation control of multi-agent system, focusing on the papers published in major control systems and robotics journals since 2007.Consensus-based formation control of multiple vehicles, including Unmanned Aerial Vehicles (UAVs), robots, and unmanned underwater vehicles, has been a very active research subject of the system control area.The recent results in this area are categorized into two directions as consensus formation producing and consensus formation following.In the end, a short discussion section is included to summarize the recent researches and to propose several vital research directions along with some problems important for further investigations.

Analysis is made to the superiority of Close-Loop Directed Infrared Countermeasures (CL-DIRCM). The research progress and the experimental verification of foreign airborne CL-DIRCM techniques are summarized and the development trend is given. The working principle and compositions of airborne CL-DIRCM are presented, with focus on the key technologies of airborne CL-DIRCM, including wide-temperature-region, high-efficiency infrared laser technology, high-precision active tracking technology, fast and accurate seeker identification technology, and laser modulated jamming technology with optimized jamming codes. The experimental verifications of the key technologies of CL-DIRCM are given.

For the issue of missile attacking the target with impact angle constraint, a finite-time convergent sliding-mode guidance law with impact angle of the constraint is put forward.First of all, the missile-target relative motion relationship is established, and the guidance law is designed based on the sliding mode variable structure theory by using a fast nonlinear terminal sliding mode surface and selecting adaptive exponential reaching law.Then, the stability of the guidance law is analyzed by using Lyapunov theory, and analysis is also made to the finite-time convergence.Saturation function is used instead of symbolic function to reduce the influence of jitter.Finally, the designed guidance law is compared with the offset proportional guidance law with fall angle constraint.Simulation shows that the designed guidance law has better performance, stronger robustness, and can achieve the requirement of the expected impact angle.

The quad-rotor UAV control system is not only complex, but also susceptible to external interference, and has poor robustness.In order to enhance the controlling precision of the quad-rotor UAV, the sliding mode variable structure control method is adopted in this paper.The quad-rotor UAV dynamic mathematical model, motor model and wind field disturbance model are built up.Then, Matlab is utilized to establish SMC controllers, and appropriate parameters and methods for vibration eliminating are selected.Therefore, the altitude and attitude of the quad-rotor UAV can be controlled.The experimental results show that the SMC controllers have fine dynamic performance and anti-disturbance performance.

Considering that the Digital Down Conversion (DDC) filtering may cause phase delay of signal, and the received Global Navigation Satellite System (GNSS) signal has Doppler frequency shift, we present here a DDC compensation technique applied to GNSS signal.Through analyzing the frequency-domain characteristic of input IF digital signal of the filter, the phase difference between the input signal and the filtered signal is obtained.The filtered signal multiplies the phase factor after FFT and then restores the original signal phase through IFFT, which can compensate the phase delay and Doppler frequency loss caused by DDC.Comparison is made to the originally received data and the one after DDC compensation, and the result shows that the code phase delay can be correctly compensated and Doppler frequency can be correctly acquired by the GNSS software receiver.

The description of Extra-Functional Properties (EFPs) is a challenge in component research.The diversity of the EFPs and their relevance to other element of the system increase the difficulty of description.Meanwhile, it is not easy to guarantee the validity and accuracy of the attribute data.Taking the above issues into consideration, we resolved the element of component to decrease complexity of the system, and introduced a EFPs model, which is normative and uniform.The accuracy of the attribute data was increased through data refining, and the validity of the value was increased through values inherited.Finally, the method for selecting multiple attribute data was given with specific examples.

Human factors have an important impact on aviation safety. The evaluation of pilot's workload is one of the most noteworthy human factor issues. In this paper, we introduce an efficient algorithm for finding the effective sparse feature Principal Component (PC) of multiple physiological signals. Sparse Principal Component Analysis (SPCA) imposes extra constraints or penalty terms to the standard Principal Component Analysis (PCA) to achieve sparsity. Experiments on multiple physiological signals datasets from flight task show that SPCA is faster than PCA, especially on large and sparse data sets, while the numerical quality of the solution is comparable to PCA algorithm and the principal components extracted by SPCA are easier to explain.

The code tracking performance assessment method for tradition navigation signal is not applicable for the L1C of new signal system in the presence of continuous wave interference.Therefore, we made a qualitative analysis to the code tracking performance of L1C signal from the perspective of pseudo code by using the odd-even correlation criterion.The assessment methods of “Interference Error Envelope” and “Average Error Envelope” were put forward for making quantitative analysis to the code tracking performance of L1C signal under interference.The result shows that the L1C signal has a better performance than C/A code signal:The code tracking performance of pilot signal is 1~1.3 (with the maximum of 1.4) times better than that of the data signal, while a very few data code signal make a better code tracking than the pilot code signal.

The VxWorks interrupt affinity is studied, and an interrupt dynamic routing method is proposed based on load balancing for improving the interrupt response rate of the multi-core processor, T1040.Analysis is made to the architecture of the multi-core programmable interrupt controller of T1040 and its working principle.And then, research is carried out on how to implement interrupt affinity in VxWorks kernel of SMP architecture based on the controller.It shows that the interrupt can be bound to specific processors to obtain the best execution performance by static and dynamic routing under multi-core environment.And an interrupt dynamic routing method is proposed based on interrupt load balancing.The experimental results on the T1040 hardware platform indicate that: The method is effective for balancing the routing interrupts across multiple cores, makes full use of processor resources and improves timeliness of system.

The suckers controlling distributor was designed for the aircraft skin detection robot based on the strategy of actuator control matrix switching. The stability and flexibility are critical for the robot’s curvature adaptive attitude control.A controlling distributor was designed to improve the stability and flexibility of robot by controlling the output of the vacuum system.First, the control allocation matrix of the controlling distributor was established based on the force analysis to the robot structure model, and thus the controlling distributor was designed.Then, considering the possible failure of the sucker system, the strategy of changing the priority of the suckers was used to change the weighting coefficient value of corresponding sucker. Actuator control matrix switching strategy was designed based on the mathematical model of suction safety gain.The improved redistributed pseudo inverse algorithm was used to solve the saturation problem and finally controlling simulations and tests were carried out to prove the feasibility of the distributor.

To design a near-optimal search path for airborne magnetic anomaly detection against a moving target, an optimum algorithm was proposed based on genetic algorithm with cumulative detection probability as fitness evaluation function.Variable-length, real-number encoding was applied to the chromosome to make it close to real search path.Priori-knowledge of the target was applied to limit the path constrains.The initial populations were generated by an initialization strategy with combination of traditional regular pattern and random search pattern, to ensure the individual diversity and high quality.In the process of genetic operator design, we carried out crossover and mutation strategy based on ellipse constraints to ensure the searcher and target follow physically realizable paths where space and time are continuous.Simulation result shows that:The proposed algorithm has rapid convergence speed and stable performance, and it can improve the overall searching effectiveness greatly.