The Bayesian approach is considered as the most general formulation of the state estimation for dynamic systems. However, most of the existing Bayesian estimators of stochastic hybrid systems only focus on the Markov jump system, few literature is related to the estimation problem of nonlinear stochastic hybrid systems with state dependent transitions. According to this problem, a new methodology which relaxes quite a restrictive assumption that the mode transition process must satisfy Markov properties is proposed. In this method, a general approach is presented to model the state dependent transitions, the state and output spaces are discreted into cell space which handles the nonlinearities and computationally intensive problem offline. Then maximum a posterior estimation is obtained by using the Bayesian theory. The efficacy of the estimator is illustrated by a simulated example.
This paper considers the uniform parallel machine scheduling problem with unequal release dates and delivery times to minimize the maximum completion time. For this NP-hard problem, the largest sum of release date, processing time and delivery time first rule is designed to determine a certain machine for each job, and the largest difference between delivery time and release date first rule is designed to sequence the jobs scheduled on the same machine, and then a novel algorithm for the scheduling problem is built. To evaluate the performance of the proposed algorithm, a lower bound for the problem is proposed. The accuracy of the proposed algorithm is tested based on the data with problem size varying from 200 jobs to 600 jobs. The computational results indicate that the average relative error between the proposed algorithm and the lower bound is only 0.667%, therefore the solutions obtained by the proposed algorithm are very accurate.
Local invariant algorithm applied in downward-looking image registration, usually computes the camera’s pose relative to visual landmarks. Generally, there are three requirements in the process of image registration when using these approaches. First, the algorithm is apt to be influenced by illumination. Second, algorithm should have less computational complexity. Third, the depth information of images needs to be estimated without other sensors. This paper investigates a famous local invariant feature named speeded up robust feature (SURF), and proposes a highspeed and robust image registration and localization algorithm based on it. With supports from feature tracking and pose estimation methods, the proposed algorithm can compute camera poses under different conditions of scale, viewpoint and rotation so as to precisely localize object’s position. At last, the study makes registration experiment by scale invariant feature transform (SIFT), SURF and the proposed algorithm, and designs a method to evaluate their performances. Furthermore, this study makes object retrieval test on remote sensing video. For there is big deformation on remote sensing frames, the registration algorithm absorbs the Kanade-Lucas-Tomasi (KLT) 3-D coplanar calibration feature tracker methods, which can localize interesting targets precisely and efficiently. The experimental results prove that the proposed method has a higher localization speed and lower localization error rate than traditional visual simultaneous localization and mapping (vSLAM) in a period of time.
To seek for lower-dimensional chaotic systems that have complex topological attractor structure with simple algebraic system structure, a new chaotic system of three-dimensional autonomous ordinary differential equations is presented. The new system has simple algebraic structure, and can display a 2-scroll attractor with complex topological structure, which is different from the Lorenz’s, Chen’s and L¨u’s attractors. By introducing a linear state feedback controller, the system can be controlled to generate a hyperchaotic attractor. The novel chaotic attractor, hyperchaotic attractor and dynamical behaviors of corresponding systems are further investigated by employing Lyapunov exponent spectrum, bifurcation diagram, Poincar′e mapping and phase portrait, etc., and then verified by simulating an experimental circuit.
Smooth support vector machine (SSVM) changs the normal support vector machine (SVM) into the unconstrained optimization by using the smooth sigmoid function. The method can be solved under the Broyden-Fletcher-Goldfarb-Shanno (BFGS) algorithm and the Newdon-Armijio (NA) algorithm easily, however the accuracy of sigmoid function is not as good as that of polynomial smooth function. Furthermore, the method cannot reduce the influence of outliers or noise in dataset. A fuzzy smooth support vector machine (FSSVM) with fuzzy membership and polynomial smooth functions is introduced into the SVM. The fuzzy membership considers the contribution rate of each sample to the optimal separating hyperplane and makes the optimization problem more accurate at the inflection point. Those changes play a positive role on trials. The results of the experiments show that those FSSVMs can obtain a better accuracy and consume the shorter time than SSVM and lagrange support vector machine (LSVM).
A novel polarimetric calibration method for new target property measurement radar system is presented.Its applica- tion in the real radar system is also discussed.The analysis indicates that instantaneous polarization radar(IPR)has inherent cross-polarization measurement error.The proposed method can effectively eliminate this error,and thus enhance the polarization scattering matrix(PSM)measurement precision.The phase error caused by digital receiver’s direct IF sampling and mixing of two orthogonal polarization channels can be removed.Consequently, the inherent error of target polarization scattering measurement of the instantaneous polarization radar system is well revised.It has good reference value for further ploarimetric calibration and high practical application prospect.
Two protocols are presented, which can make agents reach consensus while achieving and preserving the desired formation in fixed topology with and without communication timedelay for multi-agent network. First, the protocol without considering the communication time-delay is presented, and by using Lyapunov stability theory, the sufficient condition of stability for this multi-agent system is presented. Further, considering the communication time-delay, the effectiveness of the protocol based on Lyapunov-Krasovskii function is demonstrated. The main contribution of the proposed protocols is that, as well as the velocity consensus is considered, the formation control is concerned for multi-agent systems described as the second-order equations. Finally, numerical examples are presented to illustrate the effectiveness of the proposed protocols.
Technology management is recognized as a key for organizations to achieve competitiveness. How to promote an organization’s technology management capability is of great significance in creating efficiencies and achieving a competitive edge. The knowledge essence of technology management capability is introduced and then the correlation between knowledge diffusion and the development of technology management capability is discussed. Further, the basic and extended dynamic models of the development of technology management capability are constructed, and is applied into an enterprise. The results show that the dynamic models can well explain how the knowledge improves the development of technology management capability, and they can be used as an useful tool by an enterprise to promote technology management capability. Finally, the managerial implications of the models are discussed.
Efficiency and linearity of the microwave power amplifier are critical elements for mobile communication systems. A memory polynomial baseband predistorter based on an indirect learning architecture is presented for improving the linearity of an envelope tracing (ET) amplifier with application to a wireless transmitter. To deal with large peak-to-average ratio (PAR) problem, a clipping procedure for the input signal is employed. Then the system performance is verified by simulation results. For a single carrier wideband code division multiple access (WCDMA) signal of 16-quadrature amplitude modulation (16-QAM), about 2% improvement of the error vector magnitude (EVM) is achieved at an average output power of 45.5 dBm and gain of 10.6 dB, with adjacent channel leakage ratio (ACLR) of -64.55 dBc at offset frequency of 5 MHz. Moreover, a three-carrier WCDMA signal and a third-generation (3G) long term evolution (LTE) signal are used as test signals to demonstrate the performance of the proposed linearization scheme under different bandwidth signals.
The mismatch effect induced by the radial motion of a target is analyzed for linear frequency modulated (LFM) signals. Then, a novel integrated processing scheme is proposed to resolve the delay-Doppler coupling effect in LFM pulse compression. Therefore the range and radial velocity of the target can be simultaneously estimated with a narrowband LFM pulse. Finally, numerical simulation results demonstrate the effectiveness and good performance of the proposed method.
A new method to extract person-independent expression feature based on higher-order singular value decomposition (HOSVD) is proposed for facial expression recognition. Based on the assumption that similar persons have similar facial expression appearance and shape, the person-similarity weighted expression feature is proposed to estimate the expression feature of test persons. As a result, the estimated expression feature can reduce the influence of individuals caused by insufficient training data, and hence become less person-dependent. The proposed method is tested on Cohn-Kanade facial expression database and Japanese female facial expression (JAFFE) database. Person-independent experimental results show the superiority of the proposed method over the existing methods.
The operational readiness test (ORT), like weapon testing before firing, is becoming more and more important for systems used in the field. However, the test requirement of the ORT is distinctive. Specifically, the rule of selecting test items should be changed in different test turns, and whether there is a fault is more important than where the fault is. The popular dependency matrix (D-matrix) processing algorithms becomes low efficient because they cannot change their optimizing direction and spend unnecessary time on fault localization and isolation. To this end, this paper proposes a D-matrix processing algorithm named piecewise heuristic algorithm for D-matrix (PHAD). Its key idea is to use a piecewise function comprised of multiple different functions instead of the commonly used fixed function and switch subfunctions according to the test stage. In this manner, PHAD has the capability of changing optimizing direction, precisely matching the variant test requirements, and generating an efficient test sequence. The experiments on the random matrixes of different sizes and densities prove that the proposed algorithm performs better than the classical algorithms in terms of expected test cost (ETC) and other metrics. More generally, the piecewise heuristic function shows a new way to design D-matrix processing algorithm and a more flexible heuristic function to meet more complicated test requirements.
The aim of this paper is to solve the problems of multitarget tracking in clutter. Firstly, the data association of measurement-to-target is formulated as an integer programming problem. Through using the linear programming (LP) based branchand-bound method and adjusting the constraint conditions, an optimal set integer programming (OSIP) algorithm is then proposed for tracking multiple non-maneuvering targets in clutter. For the case of maneuvering targets, this paper introduces the OSIP algorithm into the filtering step of the interacting multiple model (IMM) algorithm resulting in the IMM based on OSIP algorithm. Extensive Monte Carlo simulations show that the presented algorithms can obtain superior estimations even in the case of high density noises.
The novel compensating method directly demodulates the signals without the carrier recovery processes, in which the carrier with original modulation frequency is used as the local coherent carrier. In this way, the phase offsets due to frequency shift are linear. Based on this premise, the compensation processes are: firstly, the phase offsets between the base band neighbor-symbols after clock recovery are unbiasedly estimated among the reference symbols; then, the receiving signals symbols are adjusted by the phase estimation value; finally, the phase offsets after adjusting are compensated by the least mean squares (LMS) algorithm. In order to express the compensation processes and ability clearly, the quadrature phase shift keying (QPSK) modulation signals are regarded as examples for Matlab simulation. BER simulations are carried out using the Monte-Carlo method. The learning curves are obtained to study the algorithm’s convergence ability. The constellation figures are also simulated to observe the compensation results directly.
Traditionally, beamforming using fractional Fourier transform (FrFT) involves a trial-and-error based FrFT order selection which is impractical. A new numerical order selection scheme is presented based on fractional power spectra (FrFT moment) of the linear chirp signal. This method can adaptively determine the optimum FrFT order by maximizing the second-order central FrFT moment. This makes the desired chirp signal substantially concentrated whereas the noise is rejected considerably. This improves the mean square error minimization beamformer by reducing effectively the signal-noise cross terms due to the finite data length de-correlation operation. Simulation results show that the new method works well under a wide range of signal to noise ratio and signal to interference ratio.
The globally exponential stability of nonlinear impulsive networked control systems (NINCS) with time delay and packet dropouts is investigated. By applying Lyapunov function theory, sufficient conditions on the global exponential stability are derived by introducing a comparison system and estimating the corresponding Cauchy matrix. An impulsive controller is explicitly designed to achieve exponential stability and ensure state converge with a given decay rate for the system. The Lorenz oscillator system is presented as a numerical example to illustrate the theoretical results and effectiveness of the proposed controller design procedure.
Inverse synthetic aperture radar (ISAR) imaging of ship targets is very important in the national defense. For the high maneuverability of ship targets, the Doppler frequency shift of the received signal is time-varying, which will degrade the ISAR image quality for the traditional range-Doppler (RD) algorithm. In this paper, the received signal in a range bin is characterized as the multi-component polynomial phase signal (PPS) after the motion compensation, and a new approach of time-frequency representation, generalized polynomial Wigner-Ville distribution (GPWVD), is proposed for the azimuth focusing. The GPWVD is based on the exponential matched-phase (EMP) principle. Compared with the conventional polynomial Wigner-Ville distribution (PWVD), the EMP principle transfers the non-integer lag coefficients of the PWVD to the position of the exponential of the signal, and the interpolation can be avoided completely. For the GPWVD, the cross-terms between multi-component signals can be reduced by decomposing the GPWVD into the convolution of Wigner-Ville distribution (WVD) and the spectrum of phase adjust functions. The GPWVD is used in the ISAR imaging of ship targets, and the high quality instantaneous ISAR images can be obtained. Simulation results and measurement data demonstrate the effectiveness of the proposed new method.
Usually the polarization of the interference and the target backscattering may vary constantly, so the optimal receiving polarization of the polarization filter should be recalculated, which makes the filter realization very difficult. Also the predict method of the necessary parameters is not explained in most papers, which makes the polarization filter realization impossible. A novel modified interference suppression (MIS) polarization filter is proposed, which resolves these problems by a new polarization designed strategy. The computation of this polarization filter is easy in most conditions, and the necessary parameters estimation method in real time is introduced, which makes polarization filter design possible.
This paper expresses the efficient outputs of decisionmaking unit (DMU) as the sum of “average outputs” forecasted by a GM (1, N) model and "increased outputs" which reflect the difficulty to realize efficient outputs. The increased outputs are solved by linear programming using data envelopment analysis efficiency theories, wherein a new sample is introduced whose inputs are equal to the budget in the issue No. n + 1 and outputs are forecasted by the GM (1, N) model. The shortcoming in the existing methods that the forecasted efficient outputs may be less than the possible actual outputs according to developing trends of input-output rate in the periods of pre-n is overcome. The new prediction method provides decision-makers with more decisionmaking information, and the initial conditions are easy to be given.
The group decision making problem with linguistic pref- erence relations is studied.The concept of additive consistent linguistic preference relation is defined,and then some properties of the additive consistent linguistic preference relation are studied. In order to rank the alternatives in the group decision making with the linguistic preference relations,the weighted average is first utilized to combine the group linguistic preference relations to one linguistic preference relation,and then the transformation function is proposed to transform the linguistic preference relation to the multiplicative preference relation,and thus the Saaty’s eigenvec- tor method(EM)of multiplicative preference relation is utilized to rank the alternatives in group decision making with the linguistic preference relations.Finally,an illustrative numerical example is given to verify the proposed method.A comparative study to the linguistic ordered weighted averaging(LOWA)operator method is also demonstrated.
The precision of the laser gyro used in tactical missiles is poor because of dithering frequency, actuating by vibration, shock and overload in dynamical environment. This paper introduces the transfer matrix method of the multibody system (MSTMM), establishes the dynamic model of the laser gyro strapdown inertial measure assembly aseismatic system, and analyzes the precision affected by dithering of the laser gyro and shocking of the tactical missile. And the dynamic response of the laser gyro strapdown inertial measure assembly aseismatic system is obtained by simulating the multibody system model. The simulation result indicates a theoretical idea to design the vibration isolation for the laser gyro strapdown inertial measure assembly.
A computationally efficient soft-output detector with lattice-reduction(LR)for the multiple-input multiple-output(MIMO) systems is proposed.In the proposed scheme,the sorted QR de- composition is applied on the lattice-reduced equivalent channel to obtain the tree structure.With the aid of the boundary control, the stack algorithm searches a small part of the whole search tree to generate a handful of candidate lists in the reduced lattice. The proposed soft-output algorithm achieves near-optimal perfor- mance in a coded MIMO system and the associated computational complexity is substantially lower than that of previously proposed methods.
The capability requirements of the command, control, communication, computing, intelligence, surveillance, reconnaissance (C4ISR) systems are full of uncertain and vague information, which makes it difficult to model the C4ISR architecture. The paper presents an approach to modeling the capability requirements with the fuzzy unified modeling language (UML) and building domain ontologies with fuzzy description logic (DL). The UML modeling constructs are extended according to the meta model of Department of Defense Architecture Framework to improve their domain applicability, the fuzzy modeling mechanism is introduced to model the fuzzy efficiency features of capabilities, and the capability requirement models are converted into ontologies formalized in fuzzy DL so that the model consistency and reasonability can be checked with a DL reasoning system. Finally, a case study of C4ISR capability requirements model checking is provided to demonstrate the availability and applicability of the method.
This paper proposes a modified centralized shifted Rayleigh filter (MCSRF) algorithm for tracking boost phase of ballistic missile (BM) trajectory with a highly nonlinear dynamical model based on bearings-only. This paper contributes three folds. Firstly, the mathematical model of an MCSRF for multiple passive sensors is derived. Then, minimum entropy based onedimensional optimization search to adaptively adjust the probability of the different filters for real time state estimation is deployed. Finally, the unscented transform (UT) is introduced to resolve the asymmetric state estimation problem. Simulation results show that the proposed algorithm can consecutively track the BM precisely during the boost phase. In comparison with the unscented Kalman filter (UKF) algorithm, the proposed algorithm effectively reduces the tracking position and velocity root mean square (RMS) errors, which will make more sense for early precision interception.
The electromagnetic scattering of chiral metamaterials is simulated with the Mie series method. Based on the spherical harmonics vector function in chiral metamaterials, the electromagnetic fields inside and outside of chiral metamaterials sphere are expanded. By applying the continuous boundary condition between the chiral metamaterials and surrounding medium, and the transformation from linearly to circularly polarized electric field components, the co-polarized and cross-polarized bistatic radar cross scattering (RCS) of chiral metamaterials sphere are given. How to overcome the instability of chiral metamaterials sphere of Mie series formula is discussed. The electromagnetic scattering of chiral metamaterials, normal media and metamaterials are compared. The numerical results show that the existence of chirality ξ of chiral etamaterials can decrease the bistatic RCS compared with the same size as normal media sphere.
The problem of robust H∞ guaranteed cost satisfactory fault-tolerant control with quadratic D stabilizability against actuator failures is investigated for a class of discrete-time systems with value-bounded uncertainties existing in both the state and control input matrices. Based on a more practical and general model of actuator continuous gain failures, taking the transient property, robust behaviour on H∞ performance and quadratic cost performance requirements into consideration, sufficient conditions for the existence of satisfactory fault-tolerant controller are given and the effective design steps with constraints of multiple performance indices are provided. Meanwhile, the consistency of the regional pole index, H∞ norm-bound constraint and cost performance indices is set up for fault-tolerant control. A simulation example shows the effectiveness of the proposed method.
A new approach to extraction of affine invariant features of contour image and matching strategy is proposed for shape recognition. Firstly, the centroid distance and azimuth angle of each boundary point are computed. Then, with a prior-defined angle interval, all the points in the neighbor region of the sample point are considered to calculate the average distance for eliminating noise. After that, the centroid distance ratios (CDRs) of any two opposite contour points to the barycenter are achieved as the representation of the shape, which will be invariant to affine transformation. Since the angles of contour points will change non-linearly among affine related images, the CDRs should be resampled and combined sequentially to build one-by-one matching pairs of the corresponding points. The core issue is how to determine the angle positions for sampling, which can be regarded as an optimization problem of path planning. An ant colony optimization (ACO)-based path planning model with some constraints is presented to address this problem. Finally, the Euclidean distance is adopted to evaluate the similarity of shape features in different images. The experimental results demonstrate the efficiency of the proposed method in shape recognition with translation, scaling, rotation and distortion.
For decreasing the multiple access interference of weaker signal acquisition in direct sequence spread spectrum (DSSS) systems, a new single decision algorithm is presented. The maximum value of correlation results is conventionally detected. However, there may be not only one strong peak among correlation results when the cross-correlation noise is strong enough to affect the correlation results. The proposed algorithm decreases the false alarm probability through the decision of the ratio of the maximum value and the second maximum value of the correlation results. Theoretical analysis and simulation results indicate that the proposed algorithm effectively suppresses the acquisition problem of multiple access interference in DSSS system.
The robust reliable H∞ control problem for discrete-time Markovian jump systems with actuator failures is studied. A more practical model of actuator failures than outage is considered. Based on the state feedback method, the resulting closed-loop systems are reliable in that they remain robust stochastically stable and satisfy a certain level of H∞ disturbance attenuation not only when all actuators are operational, but also in case of some actuator failures. The solvability condition of controllers can be equivalent to a feasibility problem of coupled linear matrix inequalities (LMIs). A numerical example is also given to illustrate the design procedures and their effectiveness.
To solve the multi-class fault diagnosis tasks, decision tree support vector machine (DTSVM), which combines SVM and decision tree using the concept of dichotomy, is proposed. Since the classification performance of DTSVM highly depends on its structure, to cluster the multi-classes with maximum distance between the clustering centers of the two sub-classes, genetic algorithm is introduced into the formation of decision tree, so that the most separable classes would be separated at each node of decisions tree. Numerical simulations conducted on three datasets compared with “one-against-all” and “one-against-one” demonstrate the proposed method has better performance and higher generalization ability than the two conventional methods.
The aim of this paper is to discuss the approximate rea- soning problems with interval-valued fuzzy environments based on the fully implicational idea.First,this paper constructs a class of interval-valued fuzzy implications by means of a type of impli- cations and a parameter on the unit interval,then uses them to establish fully implicational reasoning methods for interval-valued fuzzy modus ponens(IFMP)and interval-valued fuzzy modus tol- lens(IFMT)problems.At the same time the reversibility properties of these methods are analyzed and the reversible conditions are given.It is shown that the existing unified forms ofα-triple I(the abbreviation of triple implications)methods for FMP and FMT can be seen as the particular cases of our methods for IFMP and IFMT.
Frequency-invariant beamformer (FIB) design is a key issue in wideband array signal processing. To use commonly wideband linear array with tapped delay line (TDL) structure and complex weights, the FIB design is provided according to the rule of minimizing the sidelobe level of the beampattern at the reference frequency while keeping the distortionless response constraint in the mainlobe direction at the reference frequency, the norm constraint of the weight vector and the amplitude constraint of the averaged spatial response variation (SRV). This kind of beamformer design problem can be solved with the interior-point method after being converted to the form of standard second order cone programming (SOCP). The computer simulations are presented which illustrate the effectiveness of our FIB design method for the wideband linear array with TDL structure and complex weights.
Low power and real time very large scale integration (VLSI) architectures of motion estimation (ME) algorithms for mobile devices and applications are presented. The power reduction is achieved by devising a novel correction recovery mechanism based on algorithms which allow the use of reduced bit sum of absolute difference (RBSAD) metric for calculating matching error and conversion to full resolution sum of absolute difference (SAD) metric whenever necessary. Parallel and pipelined architectures for high throughput of full search ME corresponding to both the full resolution SAD and the generalized RBSAD algorithm are synthesized using Xilinx Synthesis Tools (XST), where the ME designs based on reduced bit (RB) algorithms demonstrate the reduction in power consumption up to 45% and/or the reduction in area up to 38%.
In this paper, we propose an improved YOLOv5-based object detection method for radar images, which have the characteristics of diffuse weak noise and imaging distortion. To mitigate the effects of noise without losing spatial information, an coordinate attention (CA) has been added to pre-extract the feature of the images, which can guarantee a better feature extraction ability. A new stochastic weighted average (SWA) method is designed to refine generalization ability of the algorithm, where the medium mean is used instead of their average value. By introducing an deformable convolution, both regular and irregular images can be proceeded. The experimental results show that the improved algorithm performs better in object detection of radar images compared with the YOLOv5 model, which confirms the effectiveness and feasibility of our model.
Ubiquitous radar is a new radar system that provides continuous and uninterrupted multifunction capability within a coverage volume. Continuous coverage from close-in “pop-up” targets in clutter to long-range targets impacts selection of waveform parameters. The coherent processing interval (CPI) must be long enough to achieve a certain signal-to-noise ratio (SNR) that ensures the efficiency of detection. The condition of detection in the case of low SNR is analyzed, and three different cases that would occur during integration are discussed and a method to determine the CPI is presented. The simulation results show that targets detection with SNR as low as −26 dB in the experimental system can possibly determine the CPI.
