Adaptive detection based on or thogonal par tition of the primary and secondary data

A novel adaptive detection scheme both for point-like and distributed targets in the presence of Gaussian disturbance in the partial y homogeneous environment （PHE） is proposed. The novel detection scheme is based on the orthogonal projection technique. Both the case of known covariance matrix structure and the case of unknown covariance matrix structure are con-sidered. For the former case, the closed-form statistical pro-perty of the novel detectors is derived. When the covariance matrix is unknown, the corresponding detectors have higher probabilities of detection （PDs） than their natural competitors. Moreover, they ensure constant false alarm rate （CFAR） property.     

Low side lobe pattern synthesis using projection method with genetic algorithm for truncated cone conformal phased arrays

A hybrid method for synthesizing antenna＇s three dimensional （3D） pattern is proposed to obtain the low sidelobe feature of truncated cone conformal phased arrays. In this method, the elements of truncated cone conformal phased arrays are projected to the tangent plane in one generatrix of the truncated cone. Then two dimensional （2D） Chebyshev amplitude distribution optimization is respectively used in two mutual vertical directions of the tangent plane. According to the location of the elements, the excitation current amplitude distribution of each element on the conformal structure is derived reversely, then the excitation current amplitude is further optimized by using the genetic algorithm （GA）. A truncated cone problem with 8x8 elements on it, and a 3D pattern desired side lobe level （SLL） up to 35 dB, is studied. By using the hybrid method, the optimal goal is accomplished with acceptable CPU time, which indicates that this hybrid method for the low sidelobe synthesis is feasible.     

多目标决策灰色关联投影法及其应用

运用灰色系统理论和矢量投影原理 ,提出了灰色关联投影法 ,介绍了该方法的基本原理 ,给出了灰色关联投影角、灰色关联投影值等基本概念 ,总结了用该方法进行系统分析的一般步骤 .实例研究表明 ,该方法对于综合系统评价是有效的.     

Spectral analysis and stabilization of a coupled wave-ODE system

In this paper, an interconnected wave-ODE system with K-V damping in the wave equation and unknown parameters in the ODE is considered. It is found that the spectrum of the system operator is composed of two parts： Point spectrum and continuous spectrum. The continuous spectrum consists of an isolated point 1 1/d, and there are two branches of the asymptotic eigenvalues： The first branch is accumulating towards 1 -2, and the other branch tends to -∞. It is shown that there is a sequence of generalized eigenfunctions, which forms a Riesz basis for the Hilbert state space. As a consequence, the spectrum-determined growth condition and exponential stability of the system are concluded.     

Multi-agent consensus with time-varying delays and switching topologies

The consensus problems of multi-agents with time-varying delays and switching topologies are studied. First, assume that an agent receives state information from its neighbors with fixed communication delays and processes its own state information with time-varying self-delay respectively. The state time-delay feedback is introduced into the existing consensus protocol to begenerate an improved protocol. Then a sufficient condition is derived which can make the system with time-varying self-delays achieve the consensus. On this basis, a specific form of consensus equilibrium influenced by the initial states of agents, time-delays and state feedback intensity is figured out. In addition, the multi-agent consensus is considered with time-varying topologies. Finally, simulations are presented to il ustrate the validity of theoretical results.     

Higher-order principal component pursuit via tensor approximation and convex optimization

Recovering the low-rank structure of data matrix from sparse errors arises in the principal component pursuit （PCP）. This paper exploits the higher-order generalization of matrix recovery, named higher-order principal component pursuit （HOPCP）, since it is critical in multi-way data analysis. Unlike the convexification （nuclear norm） for matrix rank function, the tensorial nuclear norm is stil an open problem. While existing preliminary works on the tensor completion field provide a viable way to indicate the low complexity estimate of tensor, therefore, the paper focuses on the low multi-linear rank tensor and adopt its convex relaxation to formulate the convex optimization model of HOPCP. The paper further propose two algorithms for HOPCP based on alternative minimization scheme： the augmented Lagrangian alternating direction method （ALADM） and its truncated higher-order singular value decomposition （ALADM-THOSVD） version. The former can obtain a high accuracy solution while the latter is more efficient to handle the computationally intractable problems. Experimental results on both synthetic data and real magnetic resonance imaging data show the applicability of our algorithms in high-dimensional tensor data processing.     

Asymptotic and stable proper ties of general stochastic functional differential equations

The asymptotic and stable properties of general stochastic functional differential equations are investigated by the multiple Lyapunov function method, which admits non-negative up-per bounds for the stochastic derivatives of the Lyapunov functions, a theorem for asymptotic properties of the LaSal e-type described by limit sets of the solutions of the equations is obtained. Based on the asymptotic properties to the limit set, a theorem of asymptotic stability of the stochastic functional differential equations is also established, which enables us to construct the Lyapunov functions more easily in application. Particularly, the wel-known classical theorem on stochastic stability is a special case of our result, the operator LV is not required to be negative which is more general to fulfil and the stochastic perturbation plays an important role in it. These show clearly the improvement of the traditional method to find the Lyapunov functions. A numerical simulation example is given to il ustrate the usage of the method.     

Interactive multigraph visualization and exploration with a two-phase strategy

While it is very reasonable to use a multigraph consisting of multiple edges between vertices to represent various relationships, the multigraph has not drawn much attention in research. To visualize such a multigraph, a clear layout representing a global structure is of great importance, and interactive visual analysis which allows the multiple edges to be adjusted in appropriate ways for detailed presentation is also essential. A novel interactive two-phase approach to visualizing and exploring multigraph is proposed. The approach consists of two phases： the first phase improves the previous popular works on force-directed methods to produce a brief drawing for the aggregation graph of the input multigraph, while the second phase proposes two interactive strategies, the magnifier model and the thematic-oriented subgraph model. The former highlights the internal details of an aggregation edge which is selected interactively by user, and draws the details in a magnifying view by cubic Bezier curves; the latter highlights only the thematic subgraph consisting of the selected multiple edges that the user concerns. The efficiency of the proposed approach is demonstrated with a real-world multigraph dataset and how it is used effectively is discussed for various potential applications.     

Spiking neural P systems with anti-spikes and without annihilating priority as number acceptors

Spiking neural P systems with anti-spikes （ASN P systems） are variant forms of spiking neural P systems, which are inspired by inhibitory impulses/spikes or inhibitory synapses. The typical feature of ASN P systems is when a neuron contains both spikes and anti-spikes, spikes and anti-spikes wil immediately annihilate each other in a maximal way. In this paper, a restricted variant of ASN P systems, cal ed ASN P systems without anni-hilating priority, is considered, where the annihilating rule is used as the standard rule, i.e., it is not obligatory to use in the neuron associated with both spikes and anti-spikes. If the annihilating rule is used in a neuron, the annihilation wil consume one time unit. As a result, such systems using two categories of spiking rules （identified by （a, a） and （a,a^-）） can achieve Turing completeness as number accepting devices.     

Multi-label dimensionality reduction and classification with extreme learning machines

In the need of some real applications, such as text categorization and image classification, the multi-label learning gradually becomes a hot research point in recent years. Much attention has been paid to the research of multi-label classification algorithms. Considering the fact that the high dimensionality of the multi-label datasets may cause the curse of dimensionality and wil hamper the classification process, a dimensionality reduction algorithm, named multi-label kernel discriminant analysis （MLKDA）, is proposed to reduce the dimensionality of multi-label datasets. MLKDA, with the kernel trick, processes the multi-label integrally and realizes the nonlinear dimensionality reduction with the idea similar with linear discriminant analysis （LDA）. In the classification process of multi-label data, the extreme learning machine （ELM） is an efficient algorithm in the premise of good accuracy. MLKDA, combined with ELM, shows a good performance in multi-label learning experiments with several datasets. The experiments on both static data and data stream show that MLKDA outperforms multi-label dimensionality reduction via dependence maximization （MDDM） and multi-label linear discriminant analysis （MLDA） in cases of balanced datasets and stronger correlation between tags, and ELM is also a good choice for multi-label classification.     

Conceptual design and RCS performance research of shipborne early warning aircraft

In order to improve the survivability of the aircraft,conceptual design and radar cross section（RCS） performance research are done. The CATIA software is used to design the 3D digital model of the shipborne early warning aircraft, and some measures are taken to reduce the RCS characteristics of the early warning aircraft at the same time. Based on the physical optics method and the equivalent electromagnetic flow method,the aircraft＇s RCS characteristics and strength distribution characteristics are simulated numerically, and compared with the foreign advanced shipborne early warning aircraft. The simulation results show that under the X radar band, when the incident wave pitching angle is 0？, compared with the foreign advanced shipborne early warning aircraft, the forward RCS average value of the conceptual shipborne early warning aircraft is reduced to 24.49%, the lateral RCS average value is reduced to 5.04%, and the backward RCS average value is reduced to 39.26%. The research results of this paper are expected to provide theoretical basis and technical support for the conceptual design and the stealth design of the shipborne early warning aircraft.     

Extended optimal guidance law with impact angle and acceleration constriants

The extended optima straints of miss distance and Schwartz inequality. To reduce guidance law with terminal conmpact angle is derived by the terminal acceleration and eliminate gravity disturbance absolutely, the object function, which designs the weight of control command to be the power function of time-to-go＇s reciprocal, is given. And the gravity is considered when building the state equation. Based on the parsing express of the guidance command change with varying time and adjoint system analysis method, the command characteristics and the non-dimensional miss distance of the guidance law are analyzed, a design principle of guidance order coefficients is discussed. Finally, based on the requirement of engineering, the method to calculate the guidance condition and maximal required acceleration of the guidance law is given. The simulation demonstrates that not only the guidance law can satisfy the terminal position and impact angle constraints, but also the terminal acceleration can be converged toward zero, which will support a good situation for the terminal angle of attacking control.     

Adaptive actuator failure compensation and disturbance rejection scheme for spacecraft

An adaptive actuator failure compensation scheme is proposed for attitude tracking control of spacecraft with unknown disturbances and uncertain actuator failures. A new feature of this adaptive control scheme is the adaptation of the failure pattern parameter estimates, as well as the failure signal parameter estimates, for direct adaptive actuator failure compensation. Based on an adaptive backstepping control design, the estimates of the disturbance parameters are used to solve the disturbance rejection problem. The unknown disturbances are compensated completely with the stability of the whole closed-loop system. The scheme is not only able to accommodate uncertain actuator failures, but also robust against unknown external disturbances. Simulation results verify the desired adaptive actuator failure compensation performance.     

Consensus algorithm for multiple quadrotor systems under fixed and switching topologies

The distributed leadless consensus problem for multiple quadrotor systems under fixed and switching topologies is investigated. The objective is to design protocols achieving consensus for networked quadrotors＇ positions and attitudes. Because the model of a quadrotor is a strong high-order nonlinear coupling system, the approach of feedback linearization is employed to transform the model into a group of four linear subsystems among which there is no coupling. Then, a consensus algorithm is proposed which consists of a local feedback controller and interactions from the finite neighbors under fixed undirected topologies. Especially, the problem of choosing the parameters in the consensus algo-rithm is also addressed, enlightened by the results of the robust control theory. Furthermore, it is proved that the proposed algo-rithm also guarantees the consensus under undirected switching topologies. Simulation results show the effectiveness of the pro- posed algorithm.     

Self-alignment of full skewed RSINS：observability analysis and full-observable Kalman filter

Traditional orthogonal strapdown inertial navigation sys-tem （SINS） cannot achieve satisfactory self-alignment accuracy in the stationary base： taking more than 5 minutes and al the iner-tial sensors biases cannot get ful observability except the up-axis accelerometer. However, the ful skewed redundant SINS （RSINS） can not only enhance the reliability of the system, but also improve the accuracy of the system, such as the initial alignment. Firstly, the observability of the system state includes attitude errors and al the inertial sensors biases are analyzed with the global perspective method： any three gyroscopes and three accelerometers can be assembled into an independent subordinate SINS （sub-SINS）;the system state can be uniquely confirmed by the coupling connec-tions of al the sub-SINSs;the attitude errors and random constant biases of al the inertial sensors are observable. However, the ran-dom noises of the inertial sensors are not taken into account in the above analyzing process. Secondly, the ful-observable Kalman filter which can be applied to the actual RSINS containing random noises is established; the system state includes the position, ve-locity, attitude errors of al the sub-SINSs and the random constant biases of the redundant inertial sensors. At last, the initial self-alignment process of a typical four-redundancy ful skewed RSINS is simulated： the horizontal attitudes （pitch, rol ） errors and yaw error can be exactly evaluated within 80 s and 100 s respectively, while the random constant biases of gyroscopes and accelero-meters can be precisely evaluated within 120 s. For the ful skewed RSINS, the self-alignment accuracy is greatly improved, mean-while the self-alignment time is widely shortened.     

Computational mission analysis and conceptual system design for super low altitude satellite

This paper deals with system engineering and design methodology for super low altitude satel ites in the view of the com-putational mission analysis. Due to the slight advance of imaging instruments, such as the focus of camera and the image element of charge coupled device （CCD）, it is an innovative and economical way to improve the camera’s resolution to enforce the satel ite to fly on the lower altitude orbit. DFH-3, the mature satel ite bus de-veloped by Chinese Academy of Space Technology, is employed to define the mass and power budgets for the computational mis-sion analysis and the detailed engineering design for super low altitude satel ites. An effective iterative algorithm is proposed to solve the ergodic representation of feasible mass and power bud-gets at the flight altitude under constraints. Besides, boundaries of mass or power exist for every altitude, where the upper boundary is derived from the maximum power, while the minimum thrust force holds the lower boundary before the power reaching the initial value. What’s more, an analytical algorithm is employed to numerical y investigate the coverage percentage over the altitude, so that the nominal altitude could be selected from al the feasi-ble altitudes based on both the mass and power budgets and the repetitive ground traces. The local time at the descending node is chosen for the nominal sun-synchronous orbit based on the average evaluation function. After determining the key orbital ele-ments based on the computational mission analysis, the detailed engineering design on the configuration and other subsystems, like power, telemetry telecontrol and communication （TT＆amp;C）, and attitude determination and control system （ADCS）, is performed based on the benchmark bus, besides, some improvements to the bus are also implemented to accommodate the flight at a super low altitude. Two operation strategies, drag-free closed-loop mode and on/off open-loop mode, are presented to maintain the satel-lite’s altitude. Final y, a flight planning schedule for the satel ite is demonstrated from its launch into the initial altitude at the very beginning to its decay to death in the end.     

Image decomposition and staircase effect reduction based on total generalized variation

Total variation （TV） is widely applied in image process-ing. The assumption of TV is that an image consists of piecewise constants, however, it suffers from the so-cal ed staircase effect. In order to reduce the staircase effect and preserve the edges when textures of image are extracted, a new image decomposition model is proposed in this paper. The proposed model is based on the to-tal generalized variation method which involves and balances the higher order of the structure. We also derive a numerical algorithm based on a primal-dual formulation that can be effectively imple-mented. Numerical experiments show that the proposed method can achieve a better trade-off between noise removal and texture extraction, while avoiding the staircase effect efficiently.     

Fast image retargeting based on strip dividing and resizing

Based on image strip dividing, an effective and fast image retargeting algorithm is proposed for resizing images. First,we construct the image energy map using gradient magnitude of the pixels and calculate the accumulated energy of each column,dividing the image into several strips by integrating similar energy columns. The reduced amount of dimension is decided in inverse proportion to the average energy for each strip. Then we retarget the image combining scaling with cropping in terms of each strip＇s reduced ratio. Experiment results show that the proposed algorithm is capable of implementing fast image retargeting and preserving both the local structures and the global visual effect of the image.     

Angular glint calculation and analysis of radar targets via adaptive cross approximation algorithm

Angular glint is a significant electromagnetic （EM） scattering signature of extended radar targets. Based on the adaptive cross approximation （ACA） algorithm accelerated method of moments （MoM） and the plane incident wave assumption, the narrowband, wideband and newly developed high-resolution range profile （HRRP） based angular glint calculation formulations are derived and applied to arbitrarily shaped three-dimensional （3D） perfectly electrical y conducting （PEC） objects. In addition, the near-field angular glint is emphasized, which is of great importance for radarseeker applications. Furthermore, with the HRRP based angular glint, an approach to rigorously determine range resolution cel s which own relatively smal er angular glint is provided. Numerical results are presented with new findings to demonstrate the usefulness of the developed formulations.     

Pseudo-noise preamble based joint frame and frequency synchronization algorithm in OFDM communication systems

Frame and frequency synchronization are essential for orthogonal frequency division multiplexing （OFDM） systems. The frame offset owing to incorrect start point position of the fast Fourier transform （FFT） window, and the carrier frequency offset （CFO） due to Doppler frequency shift or the frequency mismatch between the transmitter and receiver oscil ators, can bring severe inter-symbol interference （ISI） and inter-carrier interference （ICI） for the OFDM system. Relying on the relatively good correlation charac-teristic of the pseudo-noise （PN） sequence, a joint frame offset and normalized CFO estimation algorithm based on PN preamble in time domain is developed to realize the frame and frequency synchronization in the OFDM system. By comparison, the perfor-mances of the traditional algorithm and the improved algorithm are simulated under different conditions. The results indicate that the PN preamble based algorithm both in frame offset estimation and CFO estimation is more accurate, resource-saving and robust even under poor channel condition, such as low signal-to-noise ratio （SNR） and large normalized CFO.