鸟类铁矿物磁受体中磁赤铁矿片晶链的微磁学分析

实验表明, 自然界中许多动物能感受到磁场信息, 尤其是鸟类能够依靠地磁信息导航归巢或迁徙. 鸟类磁感受机理认为, 鸟类可以通过感受地磁场的强度与倾角建立磁地图从而进行飞行导航. 目前对鸟类用于感受磁场的磁受体的研究仍然处于探索鉴定阶段, 研究铁矿物结构是否具有在生命系统中作为磁受体的物理磁学性质有着十分重要的意义. 本文使用微磁学方法对鸟类基于铁矿物的磁感受机理中的磁赤铁矿片晶状磁受体结构进行三维模拟分析, 对其在地磁场中的畴态及对磁场信息的响应作用进行探究. 结果表明, 自然畴态为涡旋态的磁赤铁矿片晶链具有感受地磁场方向变化的能力. 关键词： 鸟类定向与导航 铁矿物磁感受机理 微磁学     

基于倒谱分析的单水听器目标运动参数估计

基于浅海射线声学多途结构,提出了一种具有高稳健性、高精度的单水听器目标运动参估计方法.针对匀速直线运动目标,综合多途时延差和运动学几何关系,构建了目标三维多途时延模型,进而获得目标运动参数与多途时延差的非线性时间映射.研究了典型水声信道的倒谱表达式,提出了利用倒谱提取多途时延差的策略.采用差分进化综合优化手段估计目标运动参数,提高了算法的稳健性.理论及仿真结果表明,倒谱的时间分辨率不受信号带宽的限制,而主要取决于信号类型和信噪比;CW信号的倒谱对多普勒不敏感;参数估计精度主要取决于时延差估计精度和参与差分进化运算的信息量,当包含有最近点信息时参数估计性能较好.水池实验结果进一步验证了方法的正确性和有效性.     

联合方位-径向速度的粒子滤波目标运动分析

纯方位目标运动分析方法要求观测平台有效机动才能估计目标运动状态,针对这一问题,联合径向速度与方位角作为测量信息对目标进行运动分析,但基于卡尔曼滤波算法进行解算需要已知粗略的目标状态初始值,且收敛时间较长、误差较大,不利于目标实时跟踪.针对以上问题,提出了一种基于粒子滤波的方位径向速度联合目标运动分析方法,建立目标运动状态分析的粒子滤波算法模型,对目标位置和速度等运动要素进行估计.在目标初始状态未知的情况下,一定程度上缩短了收敛时间,减小了估计误差,海试数据处理结果显示:相同条件下,与原有方法相比,本文所提方法收敛时间从35.1 min缩短至30.0 min;跟踪精度从6.1%提高至3.8%,且无需已知目标状态初始值。      

线性等式约束下的纯方位目标运动分析

对于匀速直线运动的声源目标,为了缩短解算目标运动要素的时间,提高解算目标运动要素的精度,本文利用距离特征量导出了不同时刻间的目标距离关系,并将该距离关系转化为状态变量的两种线性约束,即硬约束和软约束。结合伪线性法,给出了两种改进的Kalman滤波算法,在理论上证明了硬约束条件下的状态估计优于软约束条件下的状态估计,软约束条件下的状态估计优于无约束条件下的状态估计。数值模拟和实验验证表明了新方法的可行性和有效性,随着目标方位方差变大,新方法的收敛时间和精度越来越优于经典方法。     

利用频域β-warping变换的浅海修正纯方位目标运动分析方法

针对纯方位目标运动分析方法收敛时间较长的问题,提出了一种利用频域β-warping变换的浅海修正纯方位目标运动分析方法.该方法利用频域β-warping变换从声强干涉结构中提取与目标距离成线性关系的时延,进而估计距离特征量,并利用距离特征量推导得到的目标状态向量的线性约束修正纯方位扩展卡尔曼滤波算法。数值仿真结果表明,对于浅海匀速直线运动目标,在信噪比不低于8 dB的情况下,与常规纯方位扩展卡尔曼滤波算法相比,改进算法将距离估计的收敛时间由26.5 min缩短至11.5 min.在浅海水平不变波导远场条件下,该方法可以快速稳定地估计距离特征量,并能够对目标进行可靠地跟踪定位。      

基于纯方位的浅海距离特征量解算分析

目标辐射噪声的LOFAR图中的干涉条纹包含了目标的运动参数和环境信息。当LOFAR图中的干涉条纹模糊或缺失时,其中的目标距离信息将无法提取。对于匀速直线运动的声源目标,仅利用方位信息,通过构造距离特征量和目标方位的关系模型,给出了一种浅海估计距离特征量的补充方法。浅海数值仿真和实验验证表明了该方法的可行性和有效性。     

基于极大似然目标状态估计的传感器管理

依据贝叶斯概率知识,采用一种极大似然的最优化方法来估计目标运动的状态估计值。基于极大似然目标状态估计方法不仅可通过最优化策略求解目标状态估计值的显示解,还可处理各种关于观测变量和状态变量的约束条件。依据目标状态估计的误差协方差矩阵与其Fisher信息矩阵间的紧密联系,详细推导似然函数关于目标状态各个分量的偏导。采用随机离散时间系统的知识,推导出对角式Fisher信息矩阵的所有对角线上的各个元素。以Fisher信息矩阵的迹范数作为传感器管理中的最优代价函数,采用0-1整数规划算法来求解传感器的分配矩阵。最后利用某仿真算例来验证方法的有效性.     

一种多基阵机动目标被动跟踪算法

由多部声纳基阵获取的方位信息对水中机动目标的跟踪实质上是一个非线性状态估计问题,文中首先依据各基阵的方位信息,采用最小二乘法得到目标位置在各采样时刻的初步估计,然后将其作为测量值用于交互多模型算法(IMM)并结合线性卡尔曼滤波(KF)得到目标运动速度和轨迹,避免了应用非线性估计算法直接进行多个方位数据融合过程中存在的各种问题。仿真结果表明这一算法简便,与双基阵纯方位机动目标被动跟踪相比具有较快的收敛速度和较高的跟踪精度。     

基于闪动快门的互补序列对的运动模糊图像复原

针对传统曝光模式下运动模糊图像复原的病态性问题,提出了一种基于闪动快门互补序列对的运动模糊图像复原方法 .分析了闪动快门成像原理及其码字序列在频域的相关特性,结合编码序列对之间的信息互补特点,引入Golay互补序列生成理论,构建长度适中的二进制闪动快门互补序列对.互补序列对的联合调制传递函数在频域上实现了信息互补,其曲线对比单码字的调制函数具有更大的最小值和更小的方差值,且其构成了峰值-谷值对应,保证了互补图像序列能够相互补偿由于运动模糊所造成的空间信息损失.引入全变分正则化模型,构造一体化的多帧图像去模糊复原算法框架,实现清晰图像的有效获取.搭建了运动目标实拍仿真成像平台,开展了仿真和实拍运动模糊复原实验.实验结果表明,该方法能够更好地保留场景细节信息,获得高质量的运动模糊复原结果,有效改善复原过程中的负效应.相较于其他几种运动目标成像获取方式,该方法复原图像具有更好的主客观评价结果 .     

基于相位相关的匀速直线运动模糊图像位移参数估计

为估算匀速直线运动模糊图像的运动参数,提出了一种基于相位相关分析的图像配准方法。该方法利用傅里叶变换的平移特性,对产生平移的目标图像进行傅里叶变换并计算归一化互功率谱,其傅里叶逆变换对应二维脉冲函数,通过计算脉冲函数峰值坐标获取位移图像之间的亚像元级位移量。结合相位相关配准原理和线性空间不变退化模型,给出了匀速直线运动点扩散函数及其光学传递函数的数学描述;讨论了匀速直线运动模糊对相位相关配准结果的影响,证明了图像经过匀速直线运动退化后,位移图像之间归一化互功率谱具有不变性。实验结果表明：动态运动模糊图像最大检测误差为0.489 pixel,标准差为0.16 pixel。     

Antagonistic formation motion of cooperative agents

This paper investigates a new formation motion problem of a class of first-order multi-agent systems with antagonistic interactions.A distributed formation control algorithm is proposed for each agent to realize the antagonistic formation motion.A sufficient condition is derived to ensure that all of the agents make an antagonistic formation motion in a distributed manner.It is shown that all of the agents can be spontaneously divided into several groups and that agents in the same group collaborate while agents in different groups compete.Finally,a numerical simulation is included to demonstrate our theoretical results.     

Time-varying formation for general linear multi-agent systems via distributed event-triggered control under switching topologies

This paper investigates the time-varying formation problem for general linear multi-agent systems using distributed event-triggered control strategy.Different from the previous works,to achieve the desired time-varying formation,a distributed control scheme is designed in an event-triggered way,in which for each agent the controller is triggered only at its own event times.The interaction topology among agents is assumed to be switching.The common Lyapunov function as well as Riccati inequality is applied to solve the time-varying formation problem.Moreover,the Zeno behavior of triggering time sequences can be excluded for each agent.Finally,a simulation example is presented to illustrate the effectiveness of the theoretical results.     

Collective surrounding control in multi-agent networks

We study the collective encirclement control problem of a multi-agent system in this paper, where the agents move collectively to encircle the multiple targets. An algorithm is proposed and a sufficient condition is derived to realize the collective encirclement motion. Some simulation results are provided to show the effectiveness of the obtained theoretical results.     

Finite-time rotating target-encirclement motion of multi-agent systems with a leader

This paper investigates the finite-time rotating target-encirclement control problem for multi-agent systems with a leader, in which the leader can obtain the state information of the target, whereas followers cannot. A novel finite-time rotating encirclement protocol is proposed, containing the state estimators of the target and the leader. Besides, some sufficient conditions are given for achieving finite-time rotating encirclement target-tracking. The validity of the achieved results is eventually assessed by a numerical example.     

Coordinated Control of Multi-Agent Systems with a Varying-Velocity Leader and Input Saturation

In this paper, we investigate a leader-following tracking problem for multi-agent systems with bounded inputs. We propose a distributed bounded protocol for each follower to track a leader whose states may not be completely measured. We theoretically prove that each agent can follow the leader with estimable track errors. Finally, some numerical simulations are presented to illustrate our theoretical results.     

Impulsive synchronization of networked nonlinear dynamical systems

In this Letter, we investigate the problem of impulsive synchronization of networked multi-agent systems, where each agent can be modeled as an identical nonlinear dynamical system. Firstly, an impulsive control protocol is designed for network with fixed topology based on the local information of agents. Then sufficient conditions are given to guarantee the synchronization of the networked nonlinear dynamical system by using algebraic graph theory and impulsive control theory. Furthermore, how to select the discrete instants and impulsive constants is discussed. The case that the topologies of the networks are switching is also considered. Numerical simulations show the effectiveness of our theoretical results.     

Group consensus of multi-agent systems subjected to cyber-attacks

In this paper, we investigate the group consensus for leaderless multi-agent systems. The group consensus protocol based on the position information from neighboring agents is designed. The network may be subjected to frequent cyberattacks, which is close to an actual case. The cyber-attacks are assumed to be recoverable. By utilizing algebraic graph theory, linear matrix inequality(LMI) and Lyapunov stability theory, the multi-agent systems can achieve group consensus under the proposed control protocol. The sufficient conditions of the group consensus for the multi-agent networks subjected to cyber-attacks are given. Furthermore, the results are extended to the consensus issue of multiple subgroups with cyber-attacks. Numerical simulations are performed to demonstrate the effectiveness of the theoretical results.     

Distance-based formation tracking control of multi-agent systems with double-integrator dynamics

This paper addresses the distance-based formation tracking problem for a double-integrator modeled multi-agent system(MAS) in the presence of a moving leader in d-dimensional space. Under the assumption that the state of leader can be obtained over fixed graphs, a distributed distance-based control protocol is designed for each double-integrator follower agent. The protocol consists of three terms: a gradient function term, a velocity consensus term, and a leader tracking term.Different shape stabilizing functions proposed in the literature can be applied to the gradient function term. The proposed controller allows all agents to both achieve the desired shape and reach the same velocity with moving leader by controlling the distances and velocity. Finally, we analyze the local asymptotic stability of the equilibrium set with center manifold theory. We validate the effectiveness of our approach through two examples.     

Consensus pursuit of heterogeneous multi-agent systems under a directed acyclic graph

This paper is concerned with the cooperative target pursuit problem by multiple agents based on directed acyclic graph. The target appears at a random location and moves only when sensed by the agents,and agents will pursue the target once they detect its existence. Since the ability of each agent may be different,we consider the heterogeneous multi-agent systems. According to the topology of the multi-agent systems,a novel consensus-based control law is proposed,where the target and agents are modeled as a leader and followers,respectively. Based on Mason’s rule and signal flow graph analysis,the convergence conditions are provided to show that the agents can catch the target in a finite time. Finally,simulation studies are provided to verify the effectiveness of the proposed approach.     

Distributed formation control for a multi-agent system with dynamic and static obstacle avoidances

Formation control and obstacle avoidance for multi-agent systems have attracted more and more attention. In this paper, the problems of formation control and obstacle avoidance are investigated by means of a consensus algorithm. A novel distributed control model is proposed for the multi-agent system to form the anticipated formation as well as achieve obstacle avoidance. Based on the consensus algorithm, a distributed control function consisting of three terms(formation control term, velocity matching term, and obstacle avoidance term) is presented. By establishing a novel formation control matrix, a formation control term is constructed such that the agents can converge to consensus and reach the anticipated formation. A new obstacle avoidance function is developed by using the modified potential field approach to make sure that obstacle avoidance can be achieved whether the obstacle is in a dynamic state or a stationary state. A velocity matching term is also put forward to guarantee that the velocities of all agents converge to the same value. Furthermore, stability of the control model is proven. Simulation results are provided to demonstrate the effectiveness of the proposed control.