Extended Kaiman filter (EKF) is one of the most widely used methods for nonlinear system estimation. A new filtering algorithm, called particle filtering (PF) is introduced. PF can yield better performance than that of EKF, because PF does not involve the linearization approximating to nonlinear systems, that is required by the EKF. PF has been shown to be a superior alternative to the EKF in a variety of applications. The base idea of PF is the approximation of relevant probability distributions using the concepts of sequential importance sampling and approximation of probability distributions using a set of discrete random samples with associated weights. PF methods still need to be improved in the aspects of accuracy and calculating speed.

Target velocity and acceleration are two of the most important features for identification of warheads and decoys in ballistic missile defense phased array radar systems. Velocity compensation is also the necessary step for one-dimensional range profile imaging. According to the high-velocity characteristics of ballistic objects and the low data rate of phased array radars with multiple target tracking, a fine spectral line digital velocity tracking frame is presented and a new method is developed to extract velocity error and resolve the velocity ambiguity in the measurement loop. Simulation results demonstrate the effectiveness of the proposed technique.

A new kind of adaptive polarization filtering algorithm in order to suppress the angle cheating interference for the active guidance radar is presented. The polarization characteristic of the interference is dynamically tracked by using Kaiman estimator under variable environments with time. The polarization filter parameters are designed according to the polarization characteristic of the interference, and the polarization filtering is finished in the target cell. The system scheme of adaptive polarization filter is studied and the tracking performance of polarization filter and improvement of angle measurement precision are simulated. The research results demonstrate this technology can effectively suppress the an-
gle cheating interference in guidance radar and is feasible in engineering.

ECTD (erroneous cell tail drop), a buffer management optimization strategy is suggested which can improve the utilization of buffer resources in satellite ATM (asynchronous transfer mode) networks. The strategy, in which erroneous cells caused by satellite channel and the following cells that belong to the same PDU (protocol data Unit) are discarded, concerns non-real-time data services that use higher layer protocol for retransmission. Based on EPD (early packet drop) policy, mathematical models are established with and without ECTD. The numerical results show that ECTD would optimize buffer management and improve effective throughput (goodput), and the increment of goodput is relative to the CER (cell error ratio) and the PDU length. The higher their values are, the greater the increment. For example, when the average PDU length values are 30 and 90, the improvement of goodput are respectively about 4% and 10%.

An improved approach for J-value segmentation (JSEG) is presented for unsupervised color image segmentation. Instead of color quantization algorithm, an automatic classification method based on adaptive mean shift (AMS) based clustering is used for nonparametric clustering of image data set. The clustering results are used to construct Gaussian mixture modelling (GMM) of image data for the calculation of soft / value. The region growing algorithm used in JSEG is then applied in segmenting the image based on the multiscale soft /-images. Experiments show that the synergism of JSEG and the soft classification based on AMS based clustering and GMM overcomes the limitations of JSEG successfully and is more robust.

Based on the characteristics of guaranteed handover (GH) algorithm, the finite capacity in one system makes the blocking probability (PB) of GH algorithm increase rapidly in the case of high traffic load. So, when large amounts of multimedia services are transmitted via a single low earth orbit (LEO) satellite system, the PB of it is much higher. In order to solve the problem, a novel handover scheme defined by multi-tier optimal layer selection is proposed. The scheme sufficiently takes into account the characteristics of double-tier satellite network, which is constituted by LEO satellites combined with medium earth orbit (MBO) satellites, and the multimedia transmitted by such network, so it can augment this systematic capacity and effectively reduces the traffic load in the LEO which performs GH algorithm. The detailed processes are also presented. The simulation and numerical results show that the approach integrated with GH algorithm achieves a significant improvement in the PB and practicability, as compared to the single LEO layer network.

MPEG-4 fine-granularity-scalable (FGS) technology is an effective solution to resolve the network bandwidth varying because FGS provides very fine granular SNR scalability. However, this scalability is obtained with sacrifice of coding efficiency. An one-loop FGS structure is presented based on motion compensation (MC+ FGS) to improve the coding efficiency of base FGS. Then it describes and discusses the hybrid spatial-SNR FGS (FGSS) structure that extends SNR scalability of FGS to spatial scalability (spatio-SNR scalability). FGSS structure inherent the low coding effi-ciency of FGS structure. Combining MC + FGS structure with FGSS structure, a structure of MC + FGSS structure is obtained which acquires both structures' advantages and counteracts both structures' defects. Experimental results prove the MC+ FGSS structure not only obtains fine granular spatio-SNR scalability, but also achieves high coding efficiency.

A new kind of secure communication system which combines the chaotic encryption means with the conventional encryption method is discussed. With the analysis results and the experiment data, the anti-attack ability of this communication system is significantly improved compared to that of the either method. At the same time, a new method of chaotic synchronization is proposed. With a small mixed discrete chaotic signal, it is quickly to synchronize the communication and a good security performance is ensured.

Bell layered space-time architecture (BLAST) is a multi-antenna communication structure with high spectrum efficiency, and it has found wide applications in LANs and WLANs. However, its performance is much poorer than those of other space-time coding approaches. In order to improve its performance, an improved BLAST based on RAKE receiving is investigated. The new system introduces orthogonal spreading sequences (OSS) into the transmitter while retains the basic structure of BLAST. The proposed receiver suppresses interferences from other antennas by the orthogonality contained in the received signals, and extracts information from each receiving antenna by using RAKE receiving principle to construct efficient statistic decision. Simulation results show that the improved system performs well over both frequency-flat and frequency-selective fading channels.

Differential space-time (DST) modulation has been proposed recently for multiple-antenna systems over Rayleigh fading channels, where neither the transmitter nor the receiver knows the fading coefficients. Among existing schemes, differential modulation is always performed in the time domain and suffers performance degradations in frequency-selective fading channels. In order to combat the fast time and frequency-selective fading, a novel time-frequency differential space-time (TF-DST) modulation scheme, which adopts differential modulation in both time and frequency domains, is proposed for multi-antenna orthogonal frequency division multiplexing (OFDM) system. A corresponding sub-optimal yet low-complexity non-coherent detection approach is also proposed. Simulation results demonstrate that the proposed system is robust for time and frequency-selective Rayleigh fading channels.

In non-homogeneous environment, traditional space-time adaptive processing doesn't effectively suppress interference and detect target, because the secondary data don't exactly reflect the statistical characteristic of the range cell under test. A novel methodology utilizing the direct data domain approach to space-time adaptive processing (ST? P) in airborne radar non-homogeneous environments is presented. The deterministic least squares adaptive signal processing technique operates on a "snapshot-by-snapshot" basis to determine the adaptive weights for nulling interferences and estimating signal of interest (SOI). Furthermore, this approach eliminates the requirement for estimating the covariance through the data of neighboring range cell, which eliminates calculating the inverse of covariance, and can be implemented to operate in real-time. Simulation results illustrate the efficiency of interference suppression in non-homogeneous environment.

To solve the coupling effect of multiconductor transmission lines excited by external electromagnetic wave, the modified method of characteristics is proposed. The modified method of characteristics which can compute the terminal induced voltages excited by the external electromagnetic wave when the terminal networks or interconnection networks contain the dynamic elements is introduced. The simulation results indicate that the modified method can analyze the terminal induced voltages when the terminal networks or the interconnection networks contain the dynamic elements excited by the external electromagnetic wave. And the results are compared with the results acquired by FDTD method, the two results are completely same. So one effective modified method is implemented to compute the transmission lines.

A new approach to loading for orthogonal frequency division multiplexing (OFDM) system is proposed, this bit-loading algorithm assigns bits to different subchannels in order to minimize the transmit energy. In the algorithm, first most bit are allocated to each subchannels according to channel condition, Shannon formula and QoS require of the user, then the residual bit are allocated to the subchannels bit by bit. In this way the algorithm is efficient while calculation is less complex. This is the first time to load bits with the scale following Shannon formula and the algorithm is of O (4N) complexity.

Multiplicative multifractal process could well model video traffic. The multiplier distributions in the multiplicative multifractal model for video traffic are investigated and it is found that Gaussian is not suitable for describing the multipliers on the small time scales. A new statistical distribution-symmetric Pareto distribution is introduced. It is applied instead of Gaussian for the multipliers on those scales. Based on that, the algorithm is updated so that symmetric pareto distribution and Gaussian distribution are used to model video traffic but on different time scales. The simulation results demonstrate that the algorithm could model video traffic more accurately.

Alternating direction implicit finite difference time domain (ADI-FDTD) method is unconditionally stable and the maximum time step is not limited by the Courant stability condition, but rather by numerical error. Compared with the conventional FDTD method, the time step of ADI-FDTD can be enlarged arbitrarily and the CPU cost can be reduced. 2D perfectly matched layer (PML) absorbing boundary condition is proposed to truncate computation space for ADI-FDTD in dispersive media using recursive convolution (RC) method and the 2D PML formulations for dispersive media are derived. ADI-FDTD formulations for dispersive media can be obtained from the simplified PML formulations. The scattering of target in dispersive soil is simulated under sine wave and Gaussian pulse excitations and numerical results of ADI-FDTD with PML are compared with FDTD. Good agreement is observed. At the same time the CPU cost for ADI-FDTD is obviously reduced.

An optimal minimum mean square error successive interference cancellation (OMMSE SIC) scheme for Groupwise space-time block coding (G-STBC) multiple-input multiple-output (MIMO) systems is presented. In such a system, transmit antennas are partitioned into several STBC encoding groups and each group transmits independent data stream which is individually STBC encoded. On the receiver side, by exploring the temporal constraint provided by STBC, an equivalent channel model similar to the one in standard vertical Bell laboratories layered space-time (V-
BLAST) systems is generated. Then OMMSE SIC algorithm is performed to detect all the transmitted information. Simulation compares the proposed scheme with non-ordering MMSE SIC scheme and the corresponding equal data rate scheme in V-BLAST systems with the same receive antennas' number. Result shows that the proposed scheme has better performance than non-ordering MMSE SIC scheme and by introducing more transmit antennas and adopting the OMMSE SIC scheme, better performance also can be achieved than corresponding V-BLAST systems.

Aimed at solving the distance and velocity decoupling problems of a moving target in LFMCW radar signal processing, a multiple repetition frequency waveform is adopted and a Doppler frequency cluster algorithm is proposed, which is capable of re-covering true velocity from the coupled velocity estimation directly. For the resolution of multiple targets, a match algorithm based on mean square error is also proposed. The combination of the above two methods realizes distance and velocity decoupling of multiple moving targets. The result of simulation verifies the effectiveness of the methods, the velocity estimation performance of DFS algorithm is improved by 2.5 dB compared with Chinese remainder theorem.

Resource-constrained project scheduling problem(RCPSP) is an important problem in research on project management. But there has been little attention paid to the objective of minimizing activities' cost with the resource constraints that is a critical sub-problem in partner selection of construction supply chain management because the capacities of the renewable resources supplied by the partners will effect on the project scheduling. Its mathematic model is presented firstly, and analysis on the characteristic of the problem shows that the objective function is non-regular and the problem is NP-complete following which the basic idea for solution is clarified. Based on a definition of preposing activity cost matrix, a heuristic algorithm is brought forward. Analyses on the complexity of the heuristics and the result of numerical studies show that the heuristic algorithm is feasible and relatively effective.

Multi-attribute decision problems where the performances of the alternatives are random variables are considered. The suggested approach grades the probabilities of preference of one alternative over another with respect to the same attribute. Based on the graded probabilistic dominance relation, the pairwise comparison information table is defined. The global preferences of the decision maker can be seen as a rough binary relation. The present paper proposes to approximate this preference relation by means of the graded probabilistic dominance relation with respect to the subsets of attributes. At last, the method is illustrated by an example.

It is not uncommon in multiple criteria decision-making that the numerical values of alternatives of some criteria are subject to imprecision, uncertainty and indetermination and the information on weights of criteria is incomplete certain. A new multiple criteria decision- making method with incomplete certain information based on ternary AHP is proposed. This improves on Takeda's method. In this method, the ternary comparison matrix of the alternatives under each pseudo-criteria is constructed, the eigenvector associated with the maximum eigenvalue of the ternary comparison matrix is attained as to normalize priority vector of the alternatives, then the order of alternatives is obtained by solving two kinds of linear programming problems. Finally, an example is given to show the feasibility and effectiveness of the method.

The ranking problem is studied when the pairwise comparisons values are uncertain in the analytic hierarchy process (AHP). The method of constructing the judgment matrix is presented when the pairwise comparisons values are denoted by the unascertained three-valued reciprocal scales. By turning the reciprocal judgment matrix into attribute judgment matrix, the method to check the consistency of the pairwise comparisons judgment matrix and the calculation method of weighting coefficients are given. Finally, numerical examples are given to illustrate the effectiveness of the proposed method.

NCW(network centric warfare) is an information warfare concentrating on network. A global network-centric warfare architecture with OGSA grid technology is put forward, which is a four levels system including the user level, the application level, the grid middleware layer and the resource level. In grid middleware layer,based on virtual hosting environment, a BEPL4WS grid service composition method is introduced. In addition, the NCW grid service model is built with the help of Eclipse-SDK-3.0.1 and Bpws4j.

WTA (weapon-target allocation) of air defense operation is a very complicated problem and current models focus on static and restricted WTA problem mostly. Based on the dynamic characteristics of air defense operational command and decision of warships' formation, a dynamic WTA model is established. Simulation results show that switch fire and repetition fire of anti-air weapon systems affect the result of the air defense operation remarkably and the dynamic model is more satisfying than static ones. Related results are gained based on the analysis of the simulation results and the results are accordant with the intuitionistic tactical judgment. The model is some reference for the research of air defense C?I system of warships' formation.

For input saturated Hammerstein systems, the two-step predictive control strategy is adopted. The first step calculates the desired intermediate variable applying unconstrained linear model and predictive control. The second step obtains the real-time control action by solving algebraic equation and desaturation. The case of immeasurable state is considered where the observer gain matrix is solved by Sylvester equation. The sufficient closed-loop stability condition is given and the designing and tuning algorithm for the domain of attraction is proposed. The theoretical results are validated by an example.

The problem of nonlinear He? filtering for interconnected Markovian jump systems is discussed. The aim of this note is the design of a nonlinear Markovian jump filter such that the resulting error system is exponentially mean-square stable and ensures a prescribed Hoo performance. A sufficient condition for the solvability of this problem is given in terms of linear matrix inequalities(LMIs). A simulation example is presented to demonstrate the effectiveness of the proposed design approach.

From the viewpoint of continuous systems, optimal control problem is proposed for a class of controlled Hybrid dynamical systems. Then a mathematical method - HDS minimum principle is put forward, which can solve the above problem. The HDS minimum principle is proved by means of Ekeland's variational principle.

A simple method for disturbance decoupling for matrix second-order linear systems is proposed directly in matrix second-order framework via Luenberger function observers based on complete parametric eigenstructure assignment. By introducing the Hi norm of the transfer function from disturbance to estimation error, sufficient and necessary conditions for disturbance decoupling in matrix second-order linear systems are established and are arranged into constraints on the design parameters via Luenberger function observers in terms of the closed-loop eigenvalues and the group of design parameters provided by the eigenstructure assignment approach. Therefore, the disturbance decoupling problem is converted into an eigenstructure assignment problem with extra parameter constraints. A simple example is investigated to show the effect and simplicity of the approach.

An adaptive control scheme is developed for a class of single-input nonlinear systems preceded by unknown hysteresis, which is a non-differentiable and multi-value mapping nonlinearity. The controller based on the three-layer neural network (NN), whose weights are derived from Lyapunov stability analysis, guarantees closed-loop semiglobal stability and convergence of the tracking errors to a small residual set. An example is used to confirm the effectiveness of the proposed control scheme.

Integrator forwarding is a recursive nonlinear design technique for the stabilization of feed-forward systems. However, this method still has some limitation. An improved design method is proposed to extend the field of application of this technique. This method is used to design a stabilizer for the inertia wheel pendulum system. Moreover, it is shown that the control Lyapunov function which is obtained from this method can also be used to design a globally asymptotically stabilizing controller with optimality.

Networked control system is new hot-point in control engineering. A new delayed model for networked control systems is presented, based on which an LQR controller is designed. A method of delays estimation online is also given. For the difficulty on implementation of LQR in NCSs with time-variant delays, the Mamdani intelligent logic with LQR controller is addressed. The stability of the networked control system is also given. Simulation results prove that the novel controller can make the system stable and robustly preserve the performance in terms of time-variant delays.

An adaptive robust control algorithm for ship straight path control system in the presence of both modeling uncertainties and the bounded disturbances is proposed. Motivated by the backstepping approach, the algorithm is developed by using the dissipation theory, such that the resulting closed-loop system is both strictly dissipative and asymptotically adaptively stable for all admissible uncertainties. Also, it is able to steer an underactuated ship along a prescribed straight path with ultimate bounds under external disturbances induced by wave, wind and ocean current. When there are no disturbances, the straight path control can be implemented in a locally asymptotically stable manner. Simulation results on an ocean-going training ship ' YULONG' are presented to validate the effectiveness of the algorithm.

A new design scheme of decentralized model reference adaptive sliding mode controller for a class of MIMO non-linear systems with the high-order interconnections is proposed. The design is based on the universal approximation capability of the Takagi - Seguno (T-S) fuzzy systems. Motivated by the principle of certainty equivalentcontrol, a decentralized adaptive controller is designed to achieve the tracking objective without computation of the T-S fuzz ymodel. The approach does not require the upper bound of the uncertainty term to be known through some adaptive estimation. By theoretical analysis, the closed-loop fuzzy control system is proven to be globally stable in the sense that all signalsinvolved are bounded, with tracking errors converging to zero. Simulation results demonstrate the effectiveness of the approach.

In wireless ad hoc network environments, every link is wireless and every node is mobile. Those features make data lost easily as well as multicasting inefficient and unreliable. Moreover, Efficient and reliable multicast in wireless ad hoc network is a difficult issue. It is a major challenge to transmission delays and packet losses due to link changes of a multicast tree at the provision of high delivery ratio for each packet transmission in wireless ad hoc network environment. In this paper, we propose and evaluate Reliable Adaptive Multicast Protocol (RAMP) based on a relay node concept. Relay nodes are placed along the multicast tree. Data recovery is done between relay nodes. RAMP supports a reliable multicasting suitable for mobile ad hoc network by reducing the number of packet retransmissions. We compare RAMP with SRM (Scalable Reliable Multicast). Simulation results show that the RAMP has high delivery ratio and low end-to-end delay for packet transmission.

Aiming at the research that using more new knowledge to develope knowledge system with dynamic accordance, and under the background of using Fuzzy language field and Fuzzy language values structure as description framework, the generalized cell Automation that can synthetically process fuzzy indeterminacy and random indeterminacy and generalized inductive logic causal model is brought forward. On this basis, a kind of the new method that can discover causal association rules is provded. According to the causal information of standard sample space and commonly sample space, through constructing its state (abnormality) relation matrix, causal association rules can be gained by using inductive reasoning mechanism. The estimate of this algorithm complexity is given,and its validity is proved through case.

Support vector machine has become an increasingly popular tool for machine learning tasks involving classification, regression or novelty detection. Training a support vector machine requires the solution of a very large quadratic programming problem. Traditional optimization methods cannot be directly applied due to memory restrictions. Up to now, several approaches exist for circumventing the above shortcomings and work well. Another learning algorithm, particle swarm optimization, for training SVM is introduted. The method is tested on UCI datasets.

In distributed parallel server system, location and redundancy of replicas have great influence on availability and efficiency of the system. In order to improve availability and efficiency of the system, two phase decision algorithm of replica allocation is proposed. The algorithm which makes use of auto-regression model dynamically predicts the future count of READ and WRITE operation, and then determines location and redundancy of replicas by considering availability, CPU and bands of the network. The algorithm can not only ensure the requirement of availability, but also reduce the system resources consumed by all the operations in a great scale. Analysis and test show that communication complexity and time complexity of the algorithm satisfy 0( n), resource optimizing scale increases with the increase of READ count.