A target group tracking algorithm for wireless sensor networks using azimuthal angle of arrival information

<正>In this paper,we explore the technology of tracking a group of targets with correlated motions in a wireless sensor network.Since a group of targets moves collectively and is restricted within a limited region,it is not worth consuming scarce resources of sensors in computing the trajectory of each single target.Hence,in this paper,the problem is modeled as tracking a geographical continuous region covered by all targets.A tracking algorithm is proposed to estimate the region covered by the target group in each sampling period.Based on the locations of sensors and the azimuthal angle of arrival(AOA) information,the estimated region covering all the group members is obtained.Algorithm analysis provides the fundamental limits to the accuracy of localizing a target group.Simulation results show that the proposed algorithm is superior to the existing hull algorithm due to the reduction in estimation error,which is between 10%and 40%of the hull algorithm,with a similar density of sensors.And when the density of sensors increases,the localization accuracy of the proposed algorithm improves dramatically.     

Synchronization of spatiotemporal chaos in complex networks via backstepping

A backstepping approach is proposed for the synchronization of chain networks of multi-spatiotemporal chaotic systems with topologically equivalent structures.The synchronization of multi-spatiotemporal chaotic systems is implemented by adding the control only to a terminal node,and the controller is designed via a corresponding update law.The control law is applied to spatiotemporal Gray-Scott systems.Numerical results demonstrate the effectiveness and the feasibility of the proposed approach.     

Track before detect for point targets with particle filter in infrared image sequences

The problem of detecting and tracking point targets in a sequence of infrared images with very low signalto-noise ratio (SNR) is investigated in this paper. A track before detect algorithm for infrared (IR) point target is developed based on particle filter. The particle filter is used to estimate the state of the target in track stage. The unnormalized weights of the output of the filter are used to approximately construct the likelihood ratio for hypothesis test in detection stage. Experiment results with the real image sequences that SNR is about 2.0 show that the proposed algorithm can successfully detect and track point target.     

Track before detect for point targets with particle filter in infrared image sequences

The problem of detecting and tracking point targets in a sequence of infrared images with very low signalto-noise ratio (SNR) is investigated in this paper. A track before detect algorithm for infrared (IR) point target is developed based on particle filter. The particle filter is used to estimate the state of the target in track stage. The unnormalized weights of the output of the filter are used to approximately construct the likelihood ratio for hypothesis test in detection stage. Experiment results with the real image sequences that SNR is about 2.0 show that the proposed algorithm can successfully detect and track point target.     

Multi-target pursuit formation of multi-agent systems

The main goal of this paper is to design a team of agents that can accomplish multi-target pursuit formation using a developed leader--follower strategy. It is supposed that every target can accept a certain number of agents. First, each agent can automatically choose its target based on the distance from the agent to the target and the number of agents accepted by the target. In view of the fact that all agents are randomly dispersed in the workplace at the initial time, we present a numbering strategy for them. During the movement of agents, not every agent can always obtain pertinent state information about the targets. So, a developed leader--follower strategy and a pursuit formation algorithm are proposed. Under the proposed method, agents with the same target can maintain a circle formation. Furthermore, it turns out that the pursuit formation algorithm for agents to the desired formation is convergent. Simulation studies are provided to illustrate the effectiveness of the proposed method.     

Approximation-error-ADP-based optimal tracking control for chaotic systems with convergence proof

In this paper, an optimal tracking control scheme is proposed for a class of discrete-time chaotic systems using the approximation-error-based adaptive dynamic programming （ADP） algorithm. Via the system transformation, the optimal tracking problem is transformed into an optimal regulation problem, and then the novel optimal tracking control method is proposed. It is shown that for the iterative ADP algorithm with finite approximation error, the iterative performance index functions can converge to a finite neighborhood of the greatest lower bound of all performance index functions under some convergence conditions. Two examples are given to demonstrate the validity of the proposed optimal tracking control scheme for chaotic systems.     

Target detection algorithm in side-scan sonar image based on pixel importance value measurement

Side-scan sonar detection application always combines with unstable results.A two-stage novel pixel importance value measurement algorithm is proposed to stabilize the detection ability and false alarm probability simultaneously.In first stage of the algorithm,a new feature defined as pixel importance value(PIV) is proposed in terms of distances between the target pixel and each other pixels.PIV measurement of current pixel is defined as the weighted sum of all remaining segmented pixels.The wei...     

Spin-image surface matching based target recognition in laser radar range imagery

We explore the problem of in-plane rotation-invariance existing in the vertical detection of laser radar (Ladar) using the algorithm of spin-image surface matching. The method used to recognize the target in the range imagery of Ladar is time-consuming, owing to its complicated procedure, which violates the requirement of real-time target recognition in practical applications. To simplify the troublesome procedures, we improve the spin-image algorithm by introducing a statistical correlated coefficient into target recognition in range imagery of Ladar. The system performance is demonstrated on sixteen simulated noise range images with targets rotated through an arbitrary angle in plane. A high efficiency and an acceptable recognition rate obtained herein testify the validity of the improved algorithm for practical applications. The proposed algorithm not only solves the problem of in-plane rotation-invariance rationally, but also meets the real-time requirement. This paper ends with a comparison of the proposed method and the previous one.     

A new distribution scheme of decryption keys used in optical verification system with multiple-wavelength information

A new distribution scheme of decryption keys used in optical verification systems is proposed. The encryption procedure is digitally implemented with the use of an iteration algorithm in computer. Three target images corresponding to three wavelengths are encoded into three sets of phase-only masks （POMs） by a special distributing method. These three sets of POMs are assigned to three authorized users as the personal identification. A lensless optical system is used as the verification system. In the verification procedure, every two of the three authorized users can pass the verification procedure cooperatively, but only one user cannot do. Numerical simulation shows that the proposed distribution scheme of decryption keys not only can improve the security level of verification system, but also can bring convenience and flexibility for authorized users.     

Reference model based consensus control of second-order multi-agent systems

This paper deals with the consensus problem of multi-agent systems with second-order dynamics.The objective is to design algorithms such that all agents will have same positions and velocities.First,a reference model based consensus algorithm is proposed.It is proved that the consensus can be achieved if the communication graph has a spanning tree.Different from most of the consensus algorithms proposed in the literature,the parameters of the control laws are different among agents.Therefore,each agent can design its control law independently.Secondly,it gives a consensus algorithm for the case that the velocities of the agents are not available.Thirdly,the effectiveness of the input delay and the communication delay is considered.It shows that consensus can be achieved if the input delay of every agent is smaller than a bound related to parameters in its control law.Finally,some numerical examples are given to illustrate the proposed results.     

基于反演自适应动态滑模的FitzHugh-Nagumo神经元混沌同步控制

本文采用反演自适应动态滑模控制实现耦合FitzHugh-Nagumo (FHN) 神经元混沌同步. 该方法将自适应技术与反演控制方法相结合, 通过设计新型切换函数, 采用动态滑模控制律, 实现了带有不确定参数的耦合FHN神经元混沌放电同步. 研究表明该方法可以有效地削弱系统的抖振, 从而避免破坏神经元的本质特性, 且响应速度快. 仿真结果证明了该控制方法的有效性. 关键词： 自适应 动态滑模控制 FitzHugh-Nagumo神经元 混沌同步     

A linear least squares approach for evaluation of crack tip stress field parameters using DIC

In the present work, an experimental study is carried out to estimate the mixed-mode stress intensity factors (SIF) for different cracked specimen configurations using digital image correlation (DIC) technique. For the estimation of mixed-mode SIF׳s using DIC, a new algorithm is proposed for the extraction of crack tip location and coefficients in the multi-parameter displacement field equations. From those estimated coefficients, SIF could be extracted. The required displacement data surrounding the crack tip has been obtained using 2D-DIC technique. An open source 2D DIC software Ncorr is used for the displacement field extraction. The presented methodology has been used to extract mixed-mode SIF׳s for specimen configurations like single edge notch (SEN) specimen and centre slant crack (CSC) specimens made out of Al 2014-T6 alloy. The experimental results have been compared with the analytical values and they are found to be in good agreement, thereby confirming the accuracy of the algorithm being proposed.     

Adaptive synchronization control of coupled chaotic neurons in an external electrical stimulation

In this paper we present a combined algorithm for the synchronization control of two gap junction coupled chaotic FitzHugh-Nagumo (FHN) neurons in an external electrical stimulation. The controller consists of a combination of dynamical sliding mode control and adaptive backstepping control. The combined algorithm yields an adaptive dynamical sliding mode control law which has the advantage over static sliding mode-based controllers of being chattering-free, i.e., a sufficiently smooth control input signal is generated. It is shown that the proposed control scheme can not only compensate for the system uncertainty, but also guarantee the stability of the synchronized error system. In addition, numerical simulations are also performed to demonstrate the effectiveness of the proposed adaptive controller.     

Geometry of magnetic rotational (MR) band-crossing phenomenon in MR bands

In this paper, an adaptive backstepping controller has been tuned to synchronise two chaotic Colpitts oscillators in a master–slave configuration. The parameters of the controller are determined using shark smell optimisation (SSO) algorithm. Numerical results are presented and compared with those of particle swarm optimisation (PSO) algorithm. Simulation results show better performance in terms of accuracy and convergence for the proposed optimised method compared to PSO optimised controller or any non-optimised backstepping controller.     

非匹配不确定交叉严反馈超混沌系统神经网络反演同步

针对一类具有非匹配不确定性的交叉严反馈超混沌系统,提出一种基于多层前向神经网络的反演自适应同步设计方法.利用神经网络估计系统中的不确定性,运用滑模控制和交叉自适应反演控制处理系统中的非匹配不确定性及神经网络的逼近误差, 当虚拟控制项系数不过零时可保证系统的同步误差趋向于零,过零时可保证同步误差有界. 数值仿真证明了提出的控制方案的有效性.     

压电驱动快速反射镜的自适应反演滑模控制

由压电驱动器驱动的快速反射镜(FSM)广泛应用于各种精密稳定跟踪系统,FSM的控制精度决定了系统的跟踪精度。但压电驱动器具有严重的迟滞非线性干扰,针对这一缺点,应用自适应径向基RBF神经网络对迟滞干扰进行非线性逼近,并在此基础上结合滑模控制和反演法,设计了自适应反演滑模(ABSM)控制器。仿真实验表明,相对于滑模控制器,ABSM控制器的最大跟踪误差和均方根误差为分别降低了57.26%和52.53%,提高了FSM的控制精度。     

Application of spectral subtraction method on enhancement of electrolarynx speech

Although electrolarynx (EL) serves as an important method of phonation for the laryngectomees, the resulting speech is of poor intelligibility due to the presence of a steady background noise caused by the instrument, even worse in the case of additive noise. This paper investigates the problem of EL speech enhancement by taking into account the frequency-domain masking properties of the human auditory system. One approach is incorporating an auditory masking threshold (AMT) for parametric adaptation in a subtractive-type enhancement process. The other is the supplementary AMT (SAMT) algorithm, which applies a cross-correlation spectral subtraction (CCSS) approach as a post-processing scheme to enhancing EL speech dealt with the AMT method. The performance of these two algorithms was evaluated as compared to the power spectral subtraction (PSS) algorithm. The best performance of EL speech enhancement was associated with the SAMT algorithm, followed by the AMT algorithm and the PSS algorithm. Acoustic and perceptual analyses indicated that the AMT and SAMT algorithms achieved the better performances of noise reduction and the enhanced EL speech was more pleasant to human listeners as compared to the PSS algorithm.     

Control and synchronization of Chaotic Attitude Control of Satellite with Backstepping controller

A backstepping control system is proposed to control and synchronize the attitude dynamics of a satellite subjected to deterministic external perturbations which induce chaotic motion when no control is affected in this paper. The proposed method is a systematic recursive design approach based on the choice of Lyapunov functions for constructing feedback control laws. The effectiveness of the proposed control scheme is verified by the simulated results.     

Nearly Perfect Spin Conversion Based on Topological Singularity in 1D Anisotropic Photonic Crystals

Although the spin-controlled vortex generation and photonic spin-Hall effect of spin-flipped abnormal mode have been widely studied recently, the traditional method based on the metasurface is difficult to fabricate, and the efficiency of the spin-flipped abnormal mode is rather low due to process errors and intrinsic material loss. Here, a new method is proposed based on the insights into the topological singularity and special Bragger reflections resonant (BRR) mode of one-dimensional (1D) finite photonic crystals (PhCs) with anisotropic material to realize nearly perfect (100%) spin-conversion efficiency. For a finite 1D PhC with cell number N, there are 3N complete spin-conversion (CSC) and complete spin-maintained (CSM) channels. Two mechanisms of these CSC and CSM channels are revealed. The working bandwidths and the angular ranges of these CSC and CSM are also studied. Based on these theoretical findings, multi-angles and multi-frequencies perfect spin-conversion (-maintained) devices can be designed. At last, these theoretical results are confirmed by the numerical experiments based on finite-difference time-domain (FDTD) methods. This work paves the way to exploring the topological properties and polarization control of PhCs made of anisotropic dielectrics and provides a prospective method for the design of multi-channels spin optical devices.