This paper proposes a distributed nonsingular cooperative guidance law for multiple flight vehicles with Field-of-View(FOV)constraints.First,a novel time-to-go estimation is developed based on a FOV-constrained Propor...This paper proposes a distributed nonsingular cooperative guidance law for multiple flight vehicles with Field-of-View(FOV)constraints.First,a novel time-to-go estimation is developed based on a FOV-constrained Proportional Navigation Guidance(FPNG)law.Then,the FPNG law is augmented with a cooperative guidance term to achieve consensus of time-to-go with predefined-time convergence prior to the impact time.A continuous auxiliary function is introduced in the bias term to avoid the singularity of guidance command.Moreover,the proposed guidance law is extended to the three-dimensional guidance scenarios and the moving target with the help of a predicted interception point.Finally,several numerical simulations are conducted,and the results verify the effectiveness,robustness,and advantages of the proposed cooperative guidance law.展开更多
For the case that two pursuers intercept an evasive target,the cooperative strategies and state estimation methods taken by pursuers can seriously affect the guidance accuracy for the target,which performs a bang For ...For the case that two pursuers intercept an evasive target,the cooperative strategies and state estimation methods taken by pursuers can seriously affect the guidance accuracy for the target,which performs a bang For the case that two pursuers intercept an evasive target,the cooperative strategies and state estimation methods taken by pursuers can seriously affect the guidance accuracy for the target,which performs a bang-bang evasive maneuver with a random switching time.Combined Fast multiple model adaptive estimation(Fast MMAE)algorithm,the cooperative guidance law takes detection configuration affecting the accuracy of interception into consideration.Introduced the detection error model related to the line-of-sight(LOS)separation angle of two interceptors,an optimal cooperative guidance law solving the optimization problem is designed to modulate the LOS separation angle to reduce the estimation error and improve the interception performance.Due to the uncertainty of the target bang-bang maneuver switching time and the effective fitting of its multi-modal motion,Fast MMAE is introduced to identify its maneuver switching time and estimate the acceleration of the target to track and intercept the target accurately.The designed cooperative optimal guidance law with Fast MMAE has better estimation ability and interception performance than the traditional guidance law and estimation method via Monte Carlo simulation.展开更多
This paper deals with the discrete-time connected coverage problem with the constraint that only local information can be utilized for each robot. In such distributed framework, global connectivity characterized by th...This paper deals with the discrete-time connected coverage problem with the constraint that only local information can be utilized for each robot. In such distributed framework, global connectivity characterized by the second smallest eigenvalue of topology Laplacian is estimated through introducing distributed minimal-time consensus algorithm and power iteration algorithm. A self-deployment algorithm is developed to disperse the robots with the precondition that the estimated second smallest eigenvalue is positive at each time-step. Since thus connectivity constraint does not impose to preserve some certain edges, the self-deployment strategy developed in this paper reserves a sufficient degree of freedom for the motion of robots. Theoretical analysis demonstrates that each pair of neighbor robots can finally reach the largest objective distance from each other while the group keeps connected all the time, which is also shown by simulations.展开更多
The state estimation for relative motion with respect to non-cooperative spacecraft in ren- dezvous and docking （RVD） is a challenging problem. In this paper, a completely non-cooperative case is considered, which m...The state estimation for relative motion with respect to non-cooperative spacecraft in ren- dezvous and docking （RVD） is a challenging problem. In this paper, a completely non-cooperative case is considered, which means that both orbit elements and inertial tensor of target spacecraft are unknown. By formulating the equations of relative translational dynamics in the orbital plane of chaser spacecraft, the issue of unknown orbit elements is solved. And for the problem for unknown inertial tensor, we propose a novel robust estimator named interaction cubature Kalman filter （InCKF） to handle it. The novel filter consists of multiple concurrent CKFs interlacing with a max- imum a posteriori （MAP） estimator. The initial estimations provided by the multiple CKFs are used in a Bayesian framework to form description of posteriori probability about inertial tensor and the MAP estimator is applied to giving the optimal estimation. By exploiting special property of spherical-radial （SR） rule, a novel method with respect to approximating the likelihood probability of inertial tensor is presented. In addition, the issue about vision sensor＇s location inconformity with center mass of chaser spacecraft is also considered. The performance of this filter is demonstrated by the estimation problem of RVD at the final phase. And the simulation results show that the perfor- mance of InCKF is better than that of extended Kalman filter （EKF） and the estimation accuracy of oose and attitude is relatively high even in the comoletely non-coooerative case.展开更多
In this paper, we consider an amplify-and-forward （AF） cooperative communication system when the channel state information （CSI） used in relay selection differs from that during data transmission, i.e., the CSI us...In this paper, we consider an amplify-and-forward （AF） cooperative communication system when the channel state information （CSI） used in relay selection differs from that during data transmission, i.e., the CSI used in relay selection is outdated. The selected relay may not be actually the best for data transmission and the outage performance of the cooperative system will deteriorate. To improve its performance, we propose a relay selection strategy based on maximum a posteriori （MAP） estimation, where relay is selected based on predicted signal-to-noise ratio （SNR）. To reduce the computation complexity, we approximate the a posteriori probability density of SNR and obtain a closed-form predicted SNR, and a relay selection strategy based on the approximate MAP estimation （RS-AMAP） is proposed. The simulation results show that this approximation leads to trivial performance loss from the perspective of outage probability. Compared with relay selection strategies given in the literature, the outage probability is reduced largely through RS-AMAP for medium-to-large transmitting powers and medium-to-high channel correlation coefficients.展开更多
This paper proposes Symbol-based Soft Forwarding (SSF) protocol for coded transmissions which is based on a simple proposed soft symbol estimation at relay nodes. We present a simple strategy of forwarding soft inform...This paper proposes Symbol-based Soft Forwarding (SSF) protocol for coded transmissions which is based on a simple proposed soft symbol estimation at relay nodes. We present a simple strategy of forwarding soft information based on a simple linear summation of likelihood functions of each symbol. Specifically, with SSF, we demonstrate that exclusion of decoding at the relays costs no significant performance loss. To validate our claims, we examine bit error rate (BER) performance for the proposed scheme against the baseline SF scheme through computer simulations. We find that the proposed scheme can obtain considerable performance gains compared to the conventional relaying protocol.展开更多
This paper proposes the cooperative position estimation of a group of mobile robots, which pertbrms disaster relief tasks in a wide area. When searching the wide area, it becomes important to know a robot＇s position ...This paper proposes the cooperative position estimation of a group of mobile robots, which pertbrms disaster relief tasks in a wide area. When searching the wide area, it becomes important to know a robot＇s position correctly. However, for each mobile robot, it is impossible to know its own position correctly. Therefore, each mobile robot estimates its position from the data of sensor equipped on it. Generally, the sensor data is incorrect since there is sensor noise, etc. This research considers two types of the sensor data errors from omnidirectional camera. One is the error of white noise of the image captured by omnidirectional camera and so on. Another is the error of position and posture between two omnidirectional cameras. To solve the error of latter case, we proposed a self-position estimation algorithm for multiple mobile robots using two omnidirectional cameras and an accelerometer. On the other hand, to solve the error of the former case, this paper proposed an algorithm of cooperative position estimation for multiple mobile robots. In this algorithm, each mobile robot uses two omnidirectional cameras to observe the surrounding mobile robot and get the relative position between mobile robots. Each mobile robot estimates its position with only measurement data of each other mobile robots. The algorithm is based on a Bayesian filtering. Simulations of the proposed cooperative position estimation algorithm for multiple mobile robots are performed. The results show that position estimation is possible by only using measurement value from each other robot.展开更多
In this paper,we propose a cooperative guidance law aimed to achieve coordinated impact angles with limited observation on target information.The primary challenge lies in establishing an appropriate communication gra...In this paper,we propose a cooperative guidance law aimed to achieve coordinated impact angles with limited observation on target information.The primary challenge lies in establishing an appropriate communication graph among all missiles and devising an algorithm to estimate target acceleration information during engagements.To address this,we propose a specific communication topology and employ a numerical integration-based estimation method.Additionally,a distributed algorithm is introduced to facilitate consensus on target acceleration estimation.Building upon these foundations,we design an optimal-control-based distributed guidance law for each missile.Performance of the proposed guidance law is validated through numerical simulations.展开更多
In order to save energy consumption of two-way amplifier forward(AF) relaying with channel estimation error, an energy efficiency enhancement scheme is proposed in this work. Firstly, through the analysis of two-way A...In order to save energy consumption of two-way amplifier forward(AF) relaying with channel estimation error, an energy efficiency enhancement scheme is proposed in this work. Firstly, through the analysis of two-way AF relaying mode with channel estimation error, the resultant instantaneous SNRs at end nodes is obtained. Then, by using a high SNR approximation, outage possibility is acquired and its simple closed-form expression is represented. Specially, for using the energy resource more efficiently, a low-complexity power allocation and transmission mode selection policy is proposed to enhance the energy efficiency of two-way AF relay system. Finally, relay priority region is identified in which cooperative diversity energy gain can be achieved. The computer simulations are presented to verify our analytical results, indicating that the proposed policy outperforms direct transmission by an energy gain of 3 dB at the relative channel estimation error less than 0.001. The results also show that the two-way AF relaying transmission loses the two-way AF relaying transmission loses its superiority to direct transmission in terms of energy efficiency when channel estimation error reaches 0.03.展开更多
Analyzed the relation between time delay difference and time delay estimation errors, based on the principles of three-point locating, a reformed threshold method for time delay difference estimation of impulse signal...Analyzed the relation between time delay difference and time delay estimation errors, based on the principles of three-point locating, a reformed threshold method for time delay difference estimation of impulse signals, called as amendment estimation for short, is developed by introducing channel equalization technique to its conventional version, named as direct estimation in this paper, to improve the estimation stability. After inherent relationship between time delay and phase shift of signals is analyzed, an integer period error compensation method utilized the diversities of both contribution share and contribution mode of concerned estimates is proposed under the condition of high precision phase lag estimation. Finally, a cooperative multi-threshold estimation method composed of amendment and direct estimations to process impulse signals with three thresholds is established. In sea trials data tests of passive locating, this method improves the estimation precision of time delay difference efficiently. The experiments verify the theoretical predictions.展开更多
In this paper, we consider the problem of unknown parameter estimation using a set of nodes that are deployed over an area. The recently proposed distributed adaptive estimation algorithms(also known as adaptive netwo...In this paper, we consider the problem of unknown parameter estimation using a set of nodes that are deployed over an area. The recently proposed distributed adaptive estimation algorithms(also known as adaptive networks) are appealing solutions to the mentioned problem when the statistical information of the underlying process is not available or it varies over time. In this paper, our goal is to develop a new incremental least-mean square(LMS) adaptive network that considers the quality of measurements collected by the nodes. Thus, we use an adaptive combination strategy which assigns each node a step size according to its quality of measurement. The adaptive combination strategy improves the robustness of the proposed algorithm to the spatial variations of signal-to-noise ratio(SNR). The performance of our algorithm is more remarkable in inhomogeneous environments when there are some nodes with low SNRs in the network. The simulation results indicate the efficiency of the proposed algorithm.展开更多
In this paper,we investigate the distributed estimation problem of continuous-time stochastic dynamic systems over sensor networks when both the system order and parameters are unknown.We propose a local information c...In this paper,we investigate the distributed estimation problem of continuous-time stochastic dynamic systems over sensor networks when both the system order and parameters are unknown.We propose a local information criterion(LIC)based on the L_(0)penalty term.By minimizing LIC at the diffusion time instant and utilizing the continuous-time diffusion least squares algorithm,we obtain a distributed estimation algorithm to simultaneously estimate the unknown order and the parameters of the system.By dealing with the effect of the system noises and the coupling relationship between estimation of system orders and parameters,we establish the almost sure convergence results of the proposed distributed estimation algorithm.Furthermore,we give a simulation example to verify the effectiveness of the distributed algorithm in estimating the system order and parameters.展开更多
The concept of connected vehicles is with great potentials for enhancing the road transportation systems in the future. To support the functions and applications under the connected vehicles frame, the estimation of d...The concept of connected vehicles is with great potentials for enhancing the road transportation systems in the future. To support the functions and applications under the connected vehicles frame, the estimation of dynamic states of the vehicles under the cooperative environments is a fundamental issue. By integrating multiple sensors, localization modules in OBUs(on-board units) require effective estimation solutions to cope with various operation conditions. Based on the filtering estimation framework for sensor fusion, an ensemble Kalman filter(En KF) is introduced to estimate the vehicle's state with observations from navigation satellites and neighborhood vehicles, and the original En KF solution is improved by using the cubature transformation to fulfill the requirements of the nonlinearity approximation capability, where the conventional ensemble analysis operation in En KF is modified to enhance the estimation performance without increasing the computational burden significantly. Simulation results from a nonlinear case and the cooperative vehicle localization scenario illustrate the capability of the proposed filter, which is crucial to realize the active safety of connected vehicles in future intelligent transportation.展开更多
A serious threat to cognitive radio networks that sense the spectrum in a cooperative manner is the transmission of false spectrum sensing data by malicious sensor nodes. SNR fluctuations due to wireless channel effec...A serious threat to cognitive radio networks that sense the spectrum in a cooperative manner is the transmission of false spectrum sensing data by malicious sensor nodes. SNR fluctuations due to wireless channel effects complicate handling such attackers even further. This enforces the system to acquire authentication. Actually, the decision maker needs to determine the reliability or trustworthiness of the shared data. In this paper, the evaluation process is considered as an estimation dilemma on a set of evidences obtained through sensor nodes that are coordinated in an underlying wireless sensor network. Then, a likelihood-based computational trust evaluation algorithm is proposed to determine the trustworthiness of each sensor node's data. The proposed procedure just uses the information which is obtained from the sensor nodes without any presumptions about node’s reliability. Numerical results confirm the effectiveness of the algorithm in eliminating malicious nodes or faulty nodes which are not necessarily conscious attackers.展开更多
This paper proposed an algorithm on simultaneous position estimation and calibration of omnidirectional camera parameters for a group of multiple mobile robots. It is aimed at developing of exploration and information...This paper proposed an algorithm on simultaneous position estimation and calibration of omnidirectional camera parameters for a group of multiple mobile robots. It is aimed at developing of exploration and information gathering robotic system in unknown environment. Here, each mobile robot is not possible to know its own position. It can only estimate its own position by using the measurement value including white noise acquired by two omnidirectional cameras mounted on it. Each mobile robot is able to obtain the distance to those robots observed from the images of two omnidirectional cameras while making calibration during moving but not in advance. Simulation of three robots moving straightly shows the effectiveness of the proposed algorithm.展开更多
The rapid development of Internet Plus Smart Energy requires further strengthening of three kinds of interconnections based on traditional power systems: physical interconnection, information interconnection, and comm...The rapid development of Internet Plus Smart Energy requires further strengthening of three kinds of interconnections based on traditional power systems: physical interconnection, information interconnection, and commercial interconnection. Due to the integration of renewable energy, the reform of the electricity market, and the deployment of the Smart Grid, a large amount of data will be generated. Thus, it is necessary to establish a Ubiquitous Power Internet of Things (UPIoT) to realize connections among people and things, things and things, and people and people in power systems. This paper studies the concept and architecture of the UPIoT and indicates the deployment of the perception layer and network layer as the key to building UPIoT in the initial stage. As UPIoT tends to cover a wide area and produce massive and distributed data, signal processing and data analytics theories and techniques are needed to handle the data and observe the state of the large-scale system. Further studies on distributed sensing and cooperative estimation theories and techniques of UPIoT are also required. Finally, the application prospects of UPIoT and the directions for future research are discussed.展开更多
In this work, we consider an amplify-and-forward two-way multi-relay system for wireless communication and mvesngate me effect of channel estimation error on the error rate performance. With the derivation of effectiv...In this work, we consider an amplify-and-forward two-way multi-relay system for wireless communication and mvesngate me effect of channel estimation error on the error rate performance. With the derivation of effective signal-to-noise ratio at the transceiver and its probability density function, we can get approximate expression for average bit error rate. Simulation results are performed to verify the analytical results.展开更多
This study addresses the fault detection problem in multi-agent systems(MASs)with additive faults and stochastic uncertainties.The main focus is on enhancing the fault detection capability of each agent through a coop...This study addresses the fault detection problem in multi-agent systems(MASs)with additive faults and stochastic uncertainties.The main focus is on enhancing the fault detection capability of each agent through a cooperative fault detection scheme,fostering cooperation between agents in two scenarios.For Gaussian uncertainties,one scheme is developed using the maximum likelihood estimation(MLE)matching expectation maximization(EM)algorithm.Additionally,a novel cooperative fault detection scheme is introduced to handle non-Gaussian uncertainties,where the cooperation mechanism among agents is determined by approximating non-Gaussian uncertainties using the Gaussian mixture model(GMM).The effectiveness and improvements of the proposed cooperative fault detection method are validated through numerical simulations.展开更多
相对位置感知作为协同导航的核心也是车辆智能驾驶的关键技术,在车辆自组网(Vehicular Ad Hoc Networks,VANET)协同定位算法中具有重要作用。然而限于系统非线性及有色噪声干扰,相同硬件平台下的相对位置后验信息获取通常局限于一定精...相对位置感知作为协同导航的核心也是车辆智能驾驶的关键技术,在车辆自组网(Vehicular Ad Hoc Networks,VANET)协同定位算法中具有重要作用。然而限于系统非线性及有色噪声干扰,相同硬件平台下的相对位置后验信息获取通常局限于一定精度。针对上述问题,基于抗差理论提出一种Huber M估计的鲁棒容积滤波(Robust Cubature Kalman Filtering,RCKF)车辆相对位置估计算法。该算法通过结合容积法则进行非线性更新,将量测方程转换为观测量和状态预测的线性回归问题后利用M估计实现求解,通过Huber损失函数降低受干扰量测值权重实现估计性能调整。紧组合车辆相对位置估计的实验表明,与容积滤波(Cubature Kalman Filter,CKF)相比,RCKF估计结果在均方根上改善23.59%,在准确度上改善21.81%,在精度上改善27.39%,有效提高了相对位置估计精确性和鲁棒性,为车辆协同定位解决方案提供一种可供参考的系统质量控制策略。展开更多
基金supported by the National Natural Science Foundation of China(No.91216304)。
文摘This paper proposes a distributed nonsingular cooperative guidance law for multiple flight vehicles with Field-of-View(FOV)constraints.First,a novel time-to-go estimation is developed based on a FOV-constrained Proportional Navigation Guidance(FPNG)law.Then,the FPNG law is augmented with a cooperative guidance term to achieve consensus of time-to-go with predefined-time convergence prior to the impact time.A continuous auxiliary function is introduced in the bias term to avoid the singularity of guidance command.Moreover,the proposed guidance law is extended to the three-dimensional guidance scenarios and the moving target with the help of a predicted interception point.Finally,several numerical simulations are conducted,and the results verify the effectiveness,robustness,and advantages of the proposed cooperative guidance law.
基金This work was supported by the National Natural Science Foundation(NNSF)of China under grant no.61673386,62073335the China Postdoctoral Science Foundation(2017M613201,2019T120944).
文摘For the case that two pursuers intercept an evasive target,the cooperative strategies and state estimation methods taken by pursuers can seriously affect the guidance accuracy for the target,which performs a bang For the case that two pursuers intercept an evasive target,the cooperative strategies and state estimation methods taken by pursuers can seriously affect the guidance accuracy for the target,which performs a bang-bang evasive maneuver with a random switching time.Combined Fast multiple model adaptive estimation(Fast MMAE)algorithm,the cooperative guidance law takes detection configuration affecting the accuracy of interception into consideration.Introduced the detection error model related to the line-of-sight(LOS)separation angle of two interceptors,an optimal cooperative guidance law solving the optimization problem is designed to modulate the LOS separation angle to reduce the estimation error and improve the interception performance.Due to the uncertainty of the target bang-bang maneuver switching time and the effective fitting of its multi-modal motion,Fast MMAE is introduced to identify its maneuver switching time and estimate the acceleration of the target to track and intercept the target accurately.The designed cooperative optimal guidance law with Fast MMAE has better estimation ability and interception performance than the traditional guidance law and estimation method via Monte Carlo simulation.
基金the National Natural Science Foundation of China(Nos.61203073 and 61271114)the Specialized Research Fund for the Doctoral Program of Higher Education of China(No.20120075120008)the Foundation of Key Laboratory of System Control and Information Processing,Ministry of Education,China(No.SCIP2012002)
文摘This paper deals with the discrete-time connected coverage problem with the constraint that only local information can be utilized for each robot. In such distributed framework, global connectivity characterized by the second smallest eigenvalue of topology Laplacian is estimated through introducing distributed minimal-time consensus algorithm and power iteration algorithm. A self-deployment algorithm is developed to disperse the robots with the precondition that the estimated second smallest eigenvalue is positive at each time-step. Since thus connectivity constraint does not impose to preserve some certain edges, the self-deployment strategy developed in this paper reserves a sufficient degree of freedom for the motion of robots. Theoretical analysis demonstrates that each pair of neighbor robots can finally reach the largest objective distance from each other while the group keeps connected all the time, which is also shown by simulations.
基金financial support provided by the National Natural Science Foundation of China(Nos.61174037,61573115)the National Basic Research Program of China(No.2012CB821205)
文摘The state estimation for relative motion with respect to non-cooperative spacecraft in ren- dezvous and docking （RVD） is a challenging problem. In this paper, a completely non-cooperative case is considered, which means that both orbit elements and inertial tensor of target spacecraft are unknown. By formulating the equations of relative translational dynamics in the orbital plane of chaser spacecraft, the issue of unknown orbit elements is solved. And for the problem for unknown inertial tensor, we propose a novel robust estimator named interaction cubature Kalman filter （InCKF） to handle it. The novel filter consists of multiple concurrent CKFs interlacing with a max- imum a posteriori （MAP） estimator. The initial estimations provided by the multiple CKFs are used in a Bayesian framework to form description of posteriori probability about inertial tensor and the MAP estimator is applied to giving the optimal estimation. By exploiting special property of spherical-radial （SR） rule, a novel method with respect to approximating the likelihood probability of inertial tensor is presented. In addition, the issue about vision sensor＇s location inconformity with center mass of chaser spacecraft is also considered. The performance of this filter is demonstrated by the estimation problem of RVD at the final phase. And the simulation results show that the perfor- mance of InCKF is better than that of extended Kalman filter （EKF） and the estimation accuracy of oose and attitude is relatively high even in the comoletely non-coooerative case.
基金National Basic Research Program of China(No.2010CB731803)
文摘In this paper, we consider an amplify-and-forward （AF） cooperative communication system when the channel state information （CSI） used in relay selection differs from that during data transmission, i.e., the CSI used in relay selection is outdated. The selected relay may not be actually the best for data transmission and the outage performance of the cooperative system will deteriorate. To improve its performance, we propose a relay selection strategy based on maximum a posteriori （MAP） estimation, where relay is selected based on predicted signal-to-noise ratio （SNR）. To reduce the computation complexity, we approximate the a posteriori probability density of SNR and obtain a closed-form predicted SNR, and a relay selection strategy based on the approximate MAP estimation （RS-AMAP） is proposed. The simulation results show that this approximation leads to trivial performance loss from the perspective of outage probability. Compared with relay selection strategies given in the literature, the outage probability is reduced largely through RS-AMAP for medium-to-large transmitting powers and medium-to-high channel correlation coefficients.
文摘This paper proposes Symbol-based Soft Forwarding (SSF) protocol for coded transmissions which is based on a simple proposed soft symbol estimation at relay nodes. We present a simple strategy of forwarding soft information based on a simple linear summation of likelihood functions of each symbol. Specifically, with SSF, we demonstrate that exclusion of decoding at the relays costs no significant performance loss. To validate our claims, we examine bit error rate (BER) performance for the proposed scheme against the baseline SF scheme through computer simulations. We find that the proposed scheme can obtain considerable performance gains compared to the conventional relaying protocol.
文摘This paper proposes the cooperative position estimation of a group of mobile robots, which pertbrms disaster relief tasks in a wide area. When searching the wide area, it becomes important to know a robot＇s position correctly. However, for each mobile robot, it is impossible to know its own position correctly. Therefore, each mobile robot estimates its position from the data of sensor equipped on it. Generally, the sensor data is incorrect since there is sensor noise, etc. This research considers two types of the sensor data errors from omnidirectional camera. One is the error of white noise of the image captured by omnidirectional camera and so on. Another is the error of position and posture between two omnidirectional cameras. To solve the error of latter case, we proposed a self-position estimation algorithm for multiple mobile robots using two omnidirectional cameras and an accelerometer. On the other hand, to solve the error of the former case, this paper proposed an algorithm of cooperative position estimation for multiple mobile robots. In this algorithm, each mobile robot uses two omnidirectional cameras to observe the surrounding mobile robot and get the relative position between mobile robots. Each mobile robot estimates its position with only measurement data of each other mobile robots. The algorithm is based on a Bayesian filtering. Simulations of the proposed cooperative position estimation algorithm for multiple mobile robots are performed. The results show that position estimation is possible by only using measurement value from each other robot.
基金supported by the NSFC 62088101 Autonomous Intelligent Unmanned Systems,Chinaby the Zhejiang Provincial Natural Science Foundation of China(No.LR20F030003).
文摘In this paper,we propose a cooperative guidance law aimed to achieve coordinated impact angles with limited observation on target information.The primary challenge lies in establishing an appropriate communication graph among all missiles and devising an algorithm to estimate target acceleration information during engagements.To address this,we propose a specific communication topology and employ a numerical integration-based estimation method.Additionally,a distributed algorithm is introduced to facilitate consensus on target acceleration estimation.Building upon these foundations,we design an optimal-control-based distributed guidance law for each missile.Performance of the proposed guidance law is validated through numerical simulations.
基金Project(IRT0852) supported by the Program for Changjiang Scholars and Innovative Research Team in University,ChinaProject(2012CB316100) supported by the National Basic Research Program of China+2 种基金Projects(61101144,61101145) supported by the National Natural Science Foundation of ChinaProject(B08038) supported by the "111" Project,ChinaProject(K50510010017) supported by the Fundamental Research Funds for the Central Universities,China
文摘In order to save energy consumption of two-way amplifier forward(AF) relaying with channel estimation error, an energy efficiency enhancement scheme is proposed in this work. Firstly, through the analysis of two-way AF relaying mode with channel estimation error, the resultant instantaneous SNRs at end nodes is obtained. Then, by using a high SNR approximation, outage possibility is acquired and its simple closed-form expression is represented. Specially, for using the energy resource more efficiently, a low-complexity power allocation and transmission mode selection policy is proposed to enhance the energy efficiency of two-way AF relay system. Finally, relay priority region is identified in which cooperative diversity energy gain can be achieved. The computer simulations are presented to verify our analytical results, indicating that the proposed policy outperforms direct transmission by an energy gain of 3 dB at the relative channel estimation error less than 0.001. The results also show that the two-way AF relaying transmission loses the two-way AF relaying transmission loses its superiority to direct transmission in terms of energy efficiency when channel estimation error reaches 0.03.
文摘Analyzed the relation between time delay difference and time delay estimation errors, based on the principles of three-point locating, a reformed threshold method for time delay difference estimation of impulse signals, called as amendment estimation for short, is developed by introducing channel equalization technique to its conventional version, named as direct estimation in this paper, to improve the estimation stability. After inherent relationship between time delay and phase shift of signals is analyzed, an integer period error compensation method utilized the diversities of both contribution share and contribution mode of concerned estimates is proposed under the condition of high precision phase lag estimation. Finally, a cooperative multi-threshold estimation method composed of amendment and direct estimations to process impulse signals with three thresholds is established. In sea trials data tests of passive locating, this method improves the estimation precision of time delay difference efficiently. The experiments verify the theoretical predictions.
文摘In this paper, we consider the problem of unknown parameter estimation using a set of nodes that are deployed over an area. The recently proposed distributed adaptive estimation algorithms(also known as adaptive networks) are appealing solutions to the mentioned problem when the statistical information of the underlying process is not available or it varies over time. In this paper, our goal is to develop a new incremental least-mean square(LMS) adaptive network that considers the quality of measurements collected by the nodes. Thus, we use an adaptive combination strategy which assigns each node a step size according to its quality of measurement. The adaptive combination strategy improves the robustness of the proposed algorithm to the spatial variations of signal-to-noise ratio(SNR). The performance of our algorithm is more remarkable in inhomogeneous environments when there are some nodes with low SNRs in the network. The simulation results indicate the efficiency of the proposed algorithm.
基金supported by the National Key R&D Program of China(No.2018YFA0703800)the Natural Science Foundation of China(No.T2293770)+1 种基金the Strategic Priority Research Program of Chinese Academy of Sciences(No.XDA27000000)the National Science Foundation of Shandong Province(No.ZR2020ZD26).
文摘In this paper,we investigate the distributed estimation problem of continuous-time stochastic dynamic systems over sensor networks when both the system order and parameters are unknown.We propose a local information criterion(LIC)based on the L_(0)penalty term.By minimizing LIC at the diffusion time instant and utilizing the continuous-time diffusion least squares algorithm,we obtain a distributed estimation algorithm to simultaneously estimate the unknown order and the parameters of the system.By dealing with the effect of the system noises and the coupling relationship between estimation of system orders and parameters,we establish the almost sure convergence results of the proposed distributed estimation algorithm.Furthermore,we give a simulation example to verify the effectiveness of the distributed algorithm in estimating the system order and parameters.
基金Project(4144081)supported by Beijing Natural Science Foundation,ChinaProjects(61403021,U1334211,61490705)supported by the National Natural Science Foundation of China+1 种基金Project(2015RC015)supported by the Fundamental Research Funds for Central Universities,ChinaProject supported by the Foundation of Beijing Key Laboratory for Cooperative Vehicle Infrastructure Systems and Safety Control,China
文摘The concept of connected vehicles is with great potentials for enhancing the road transportation systems in the future. To support the functions and applications under the connected vehicles frame, the estimation of dynamic states of the vehicles under the cooperative environments is a fundamental issue. By integrating multiple sensors, localization modules in OBUs(on-board units) require effective estimation solutions to cope with various operation conditions. Based on the filtering estimation framework for sensor fusion, an ensemble Kalman filter(En KF) is introduced to estimate the vehicle's state with observations from navigation satellites and neighborhood vehicles, and the original En KF solution is improved by using the cubature transformation to fulfill the requirements of the nonlinearity approximation capability, where the conventional ensemble analysis operation in En KF is modified to enhance the estimation performance without increasing the computational burden significantly. Simulation results from a nonlinear case and the cooperative vehicle localization scenario illustrate the capability of the proposed filter, which is crucial to realize the active safety of connected vehicles in future intelligent transportation.
文摘A serious threat to cognitive radio networks that sense the spectrum in a cooperative manner is the transmission of false spectrum sensing data by malicious sensor nodes. SNR fluctuations due to wireless channel effects complicate handling such attackers even further. This enforces the system to acquire authentication. Actually, the decision maker needs to determine the reliability or trustworthiness of the shared data. In this paper, the evaluation process is considered as an estimation dilemma on a set of evidences obtained through sensor nodes that are coordinated in an underlying wireless sensor network. Then, a likelihood-based computational trust evaluation algorithm is proposed to determine the trustworthiness of each sensor node's data. The proposed procedure just uses the information which is obtained from the sensor nodes without any presumptions about node’s reliability. Numerical results confirm the effectiveness of the algorithm in eliminating malicious nodes or faulty nodes which are not necessarily conscious attackers.
文摘This paper proposed an algorithm on simultaneous position estimation and calibration of omnidirectional camera parameters for a group of multiple mobile robots. It is aimed at developing of exploration and information gathering robotic system in unknown environment. Here, each mobile robot is not possible to know its own position. It can only estimate its own position by using the measurement value including white noise acquired by two omnidirectional cameras mounted on it. Each mobile robot is able to obtain the distance to those robots observed from the images of two omnidirectional cameras while making calibration during moving but not in advance. Simulation of three robots moving straightly shows the effectiveness of the proposed algorithm.
基金Supported by National Key Research and DevelopmentProgram of China(2016YFB0900100).
文摘The rapid development of Internet Plus Smart Energy requires further strengthening of three kinds of interconnections based on traditional power systems: physical interconnection, information interconnection, and commercial interconnection. Due to the integration of renewable energy, the reform of the electricity market, and the deployment of the Smart Grid, a large amount of data will be generated. Thus, it is necessary to establish a Ubiquitous Power Internet of Things (UPIoT) to realize connections among people and things, things and things, and people and people in power systems. This paper studies the concept and architecture of the UPIoT and indicates the deployment of the perception layer and network layer as the key to building UPIoT in the initial stage. As UPIoT tends to cover a wide area and produce massive and distributed data, signal processing and data analytics theories and techniques are needed to handle the data and observe the state of the large-scale system. Further studies on distributed sensing and cooperative estimation theories and techniques of UPIoT are also required. Finally, the application prospects of UPIoT and the directions for future research are discussed.
基金supported by National Basic Research Program of China (2009CB320401)the National Key Scientific and Technological Project of China (2010ZX03003-001)+1 种基金Doctoral Fund of Ministry of Education of China (20090005110003)the Fundamental Research Funds for the Central Universities (BUPT2009RC0111)
文摘In this work, we consider an amplify-and-forward two-way multi-relay system for wireless communication and mvesngate me effect of channel estimation error on the error rate performance. With the derivation of effective signal-to-noise ratio at the transceiver and its probability density function, we can get approximate expression for average bit error rate. Simulation results are performed to verify the analytical results.
基金supported in part by the National Natural Science Foundation of China under Grant Nos.62103304 and 62177036Shanghai Sailing Program under Grant No.21YF1450500+1 种基金Shanghai Municipal Science and Technology Major Project under Grant No.2021SHZDZX0100Shanghai Municipal Commission of Science and Technology Project under Grant No.19511132101。
文摘This study addresses the fault detection problem in multi-agent systems(MASs)with additive faults and stochastic uncertainties.The main focus is on enhancing the fault detection capability of each agent through a cooperative fault detection scheme,fostering cooperation between agents in two scenarios.For Gaussian uncertainties,one scheme is developed using the maximum likelihood estimation(MLE)matching expectation maximization(EM)algorithm.Additionally,a novel cooperative fault detection scheme is introduced to handle non-Gaussian uncertainties,where the cooperation mechanism among agents is determined by approximating non-Gaussian uncertainties using the Gaussian mixture model(GMM).The effectiveness and improvements of the proposed cooperative fault detection method are validated through numerical simulations.
文摘相对位置感知作为协同导航的核心也是车辆智能驾驶的关键技术,在车辆自组网(Vehicular Ad Hoc Networks,VANET)协同定位算法中具有重要作用。然而限于系统非线性及有色噪声干扰,相同硬件平台下的相对位置后验信息获取通常局限于一定精度。针对上述问题,基于抗差理论提出一种Huber M估计的鲁棒容积滤波(Robust Cubature Kalman Filtering,RCKF)车辆相对位置估计算法。该算法通过结合容积法则进行非线性更新,将量测方程转换为观测量和状态预测的线性回归问题后利用M估计实现求解,通过Huber损失函数降低受干扰量测值权重实现估计性能调整。紧组合车辆相对位置估计的实验表明,与容积滤波(Cubature Kalman Filter,CKF)相比,RCKF估计结果在均方根上改善23.59%,在准确度上改善21.81%,在精度上改善27.39%,有效提高了相对位置估计精确性和鲁棒性,为车辆协同定位解决方案提供一种可供参考的系统质量控制策略。
