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Simultaneous distributed localization and formation tracking control via matrix-weighted position constraints

AUTOMATICA 2025年 175卷

作者： Fang, Xu Xie, Lihua Dimarogonas, Dimos V. Dalian Univ Technol Key Lab Intelligent Control & Optimizat Ind Equipm Minist Educ Dalian 116024 Peoples R China Nanyang Technol Univ Sch Elect & Elect Engn Singapore 639798 Singapore KTH Royal Inst Technol Sch Elect Engn & Comp Sci SE-10044 Stockholm Sweden

This paper studies the problem of 3-D relative-measurement-based leader-follower simultaneous distributed localization and formation tracking control. The position information is only available to the leaders, and the followers have inter-agent relative measurements and communication with their neighbors. The key contribution is the development of a weight-matrix-based position constraint, which can make use of relative measurements such as bearing, ratio-of-distance, angle, distance, relative position and their mixture to describe the position relationship among each follower and its neighbors in 3-D space. A bearing-based distributed protocol is proposed for each follower to estimate its position and track its target position, which can drive the followers from their unlocalizable positions to localizable positions. The proposed algorithm is then extended to the case that both bearing and ratio-of-distance measurements are available, where the followers are localizable at all times if the followers and their neighbors are not collocated. In addition, the proposed method is also applicable to homogeneous or heterogeneous angle, distance, and relative position measurements as the ratio-of-distances or bearings can be obtained indirectly by these relative measurements. A remarkable advantage is that the proposed method can be implemented without persistently exciting motions. Some illustrative simulations are presented to verify the theoretical results. (c) 2025 Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies.

关键词： Formation tracking control distributed localization Bearing Ratio-of-distance Multi-agent system 3-D space

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Barycentric Coordinate-Based distributed localization for Wireless Sensor Networks Under False-Data-Injection Attacks

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IEEE TRANSACTIONS ON CYBERNETICS 2025年第4期55卷 1568-1579页

作者： Shi, Lei Chen, Xinming Zhou, Yi Henan Univ Sch Artificial Intelligence Zhengzhou 450046 Henan Peoples R China Henan Univ Int Joint Res Lab Cooperat Vehicular Networks Hena Zhengzhou 450046 Peoples R China AVIC Chengdu Aircraft Design & Res Inst Chengdu 610041 Peoples R China

localization security is crucial to the widespread applications of wireless sensor networks (WSNs) in various fields. This article mainly studies the issue of distributed localization in WSNs subject to deception attacks, in which the attacker randomly compromises communication channels and injects false data, resulting in the codification of data received by sensor nodes. A distributed iterative localization algorithm based on detection-holding strategy is proposed with the help of barycentric coordinate representations. This algorithm detects modified data in communication links through residual detection and communication encryption. It is proved theoretically that the proposed localization algorithm can achieve accurate convergence to the sensors' locations under general random false-data-injection attacks. Finally, the algorithm performance is demonstrated through simulation examples.

关键词： Location awareness Sensors Wireless sensor networks Accuracy Iterative algorithms Convex hulls Convergence Sparse matrices Position measurement Research and development distributed localization false-data-injection (FDI) attacks wireless sensor networks (WSNs)

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distributed localization with mixed measurements under switching topologies

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AUTOMATICA 2017年 76卷 251-257页

作者： Lin, Zhiyun Han, Tingrui Zheng, Ronghao Yu, Changbin Hangzhou Dianzi Univ Hangzhou 310018 Zhejiang Peoples R China Zhejiang Univ Coll Elect Engn State Key Lab Ind Control Technol Hangzhou Zhejiang Peoples R China Zhejiang Prov Marine Renewable Energy Elect Equip Hangzhou Zhejiang Peoples R China Australian Natl Univ Canberra ACT 2601 Australia NICTA Ltd Canberra ACT 2601 Australia

This paper investigates the distributed localization problem of sensor networks with mixed measurements. Each node holds a local coordinate system without a common orientation and is capable of measuring only one type of information (either distance, bearing, or relative position) to near-by nodes. Thus, three types of measurements are mixed in the sensor networks. Moreover, the communication topologies in the sensor networks may be time-varying due to unreliable communications. This paper develops a fully distributed algorithm called BCDL (Barycentric Coordinate based distributed localization) where each node starts from a random initial guess about its true coordinate and converges to the true coordinate via only local node interactions. The key idea in BCDL is to establish a unified linear equation constraints for the sensor coordinates by using the barycentric coordinates of each node with respect to its neighbors though the sensor nodes may have different types of measurements. Then a distributed iterative algorithm is proposed to solve the linear equations under time-varying communication networks. A necessary and sufficient graphical condition is obtained to ensure global convergence of the distributed, algorithm. (C) 2016 Elsevier Ltd. All rights reserved.

关键词： distributed localization Sensor network Robot network

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distributed localization Estimation for Dynamic Multiagent Systems

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IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS 2023年第4期19卷 5797-5808页

作者： Lv, Yunkai Zhang, Hao Wang, Zhuping Su, Shun-Feng Tongji Univ Dept Control Sci & Engn Shanghai 200092 Peoples R China Natl Taiwan Univ Sci & Technol Dept Elect Engn Taipei 106 Taiwan

This article investigates the real-time localization problem of dynamic multiagent systems with repetitive operation characteristics under directed graph. A distributed localization estimation algorithm based on iterative learning is proposed. The barycentric coordinates calculated based on the relative distance are used to estimate the real coordinates of the agent. Different from the traditional estimation methods along the time axis, the proposed method utilizes the information of iteration axis simultaneously. In this method, the current estimation coordinates are updated by using the estimation coordinates of the same sampling time in previous iteration, the estimation accuracy is improved, and the velocity constraint is removed. Additionally, the real-time localization problem of dynamic multiagent systems under arbitrary deployment is concerned. An improved distributed localization estimation algorithm with signed coefficients based on iterative learning is proposed. Meanwhile, the results are also extended to the localization estimation of multiagent systems with arbitrary deployment in 3-D space. By introducing Richardson iteration and infinite norm, the global asymptotic convergence of the proposed methods is guaranteed. Finally, numerical simulations and the Qbot-2e robot experiment are provided to show the effectiveness and validity of the obtained results.

关键词： Arbitrary deployment barycentric coor-dinates directed graph distributed localization iterative learning

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distributed localization Based on Signal Propagation Loss for Underwater Sensor Networks

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IEEE ACCESS 2019年 7卷 112985-112995页

作者： Qiao, Gang Zhao, Chen Zhou, Feng Ahmed, Niaz Harbin Engn Univ Acoust Sci & Technol Lab Harbin 150001 Heilongjiang Peoples R China Harbin Engn Univ Key Lab Marine Informat Acquisit & Secur Minist Ind & Informat Technol Harbin 150001 Heilongjiang Peoples R China Harbin Engn Univ Coll Underwater Acoust Engn Harbin 150001 Heilongjiang Peoples R China

localization technology for Underwater Wireless Sensor Networks (UWSNs) plays an important role in detection and navigation for underwater vehicles. In this paper, we therefore propose a novel localization scheme for UWSNs based on the propagation loss, named Communication Signal Propagation Loss localization Scheme (CSPLLS). CSPLLS is a cooperative, passive, asynchronously distributed localization method where the target only uses communication signal's strength from anchor nodes. The method is appropriate for a long-distance and large-scale positioning in shallow sea. Main innovative point of the research is to locate with a new rang-based method using signal propagation loss. Experiment and simulation results are presented in the paper which confirms that the proposed scheme provides a relatively high precision of as low as 2.2% positioning error with centroid optimization. Major advantages of this method includes: 1) getting rid of clock resources usually used in each node for localization, 2) reducing the total localization time, 3) saving the energy of each node which prolongs the lifetime of networks and 4) realize the design of underwater communication and localization integration.

关键词： Underwater localization underwater wireless sensor networks sound propagation loss distributed localization

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distributed localization of Target for MIMO Radar With Widely Separated Directional Transmitters and Omnidirectional Receivers

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IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS 2023年第3期59卷 3171-3187页

作者： Xiong, Kui Cui, Guolong Yi, Wei Wang, Shiyuan Kong, Lingjiang Univ Elect Sci & Technol China Sch Informat & Commun Engn Chengdu 611731 Peoples R China Southwest Univ Coll Elect & Informat Engn Chongqing 400715 Peoples R China

Conventional target localization algorithms for the multiple-input multiple-output (MIMO) radar with widely separated antennas are mainly based on the centralized localization framework, which suffer from huge burdens of computation and communication as well as robustness defect in complex environments. To overcome these issues, this article first considers the MIMO radar with widely separated directional transmitters and omnidirectional receivers generating the bistatic range (BR) and angle of incidence (AOI) measurements for target localization, which is proven that the position of the target can be uniquely determined with one transmitter and one receiver. Then, the distributed localization framework using the hybrid BR and AOI measurements is developed, where each receiver acts as a fusion center extracting the BR and AOI measurements to perform the localization process, and the localization problem is formulated as solving a linear matrix equation. The distributed constrained total least squares (DCTLS) algorithm considering errors in both data matrix and observation vector is proposed for each receiver for target localization. The localization performance regarding the Cramer-Rao lower bound is derived for theoretical analysis. Numerical simulations are performed to validate the efficacy and superiority of the proposed DCTLS algorithm over other typical localization algorithms.

关键词： Receivers Transmitters MIMO radar Radar Antenna measurements Position measurement Wireless sensor networks Angle of incidence (AOI) bistatic range (BR) constrained total least squares (LS) distributed localization multiple-input multiple-output (MIMO) radar

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distributed localization using Levenberg-Marquardt algorithm

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EURASIP JOURNAL ON ADVANCES IN SIGNAL PROCESSING 2021年第1期2021卷 1-26页

作者： Ahmadi, Shervin Parvini Hansson, Anders Pakazad, Sina Khoshfetrat Linkoping Univ Dept Elect Engn Linkoping Sweden C3 Ai Redwood City CA USA

In this paper, we propose a distributed algorithm for sensor network localization based on a maximum likelihood formulation. It relies on the Levenberg-Marquardt algorithm where the computations are distributed among different computational agents using message passing, or equivalently dynamic programming. The resulting algorithm provides a good localization accuracy, and it converges to the same solution as its centralized counterpart. Moreover, it requires fewer iterations and communications between computational agents as compared to first-order methods. The performance of the algorithm is demonstrated with extensive simulations in Julia in which it is shown that our method outperforms distributed methods that are based on approximate maximum likelihood formulations.

关键词： distributed localization Maximum likelihood estimation Message passing Dynamic programming Levenberg-Marquardt Nonlinear least-squares

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distributed localization for IoT with multi-agent reinforcement learning

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NEURAL COMPUTING & APPLICATIONS 2022年第9期34卷 7227-7240页

作者： Jia, Jie Yu, Ruoying Du, Zhenjun Chen, Jian Wang, Qinghu Wang, Xingwei Northeastern Univ Sch Comp Sci & Engn Shenyang 110819 Peoples R China Minist Educ Engn Res Ctr Secur Technol Complex Network Syst Shenyang 110819 Peoples R China SIASUN Robot & Automat CO Ltd Shenyang Peoples R China

localization has become one of the important techniques for Internet of Things (IoT). However, most existing localization methods need a central controller and operate on an off-line manner, which cannot satisfy the requirements of real-time IoT applications. In order to address this issue, a novel distributed localization scheme based on multi-agent reinforcement learning (MARL) is proposed. The localization problem is first reformulated as a stochastic game for maximizing the sum of the negative localization error. Each non-anchor node is then modeled as an intelligent agent, where its action space corresponds to possible locations. After that, we invoke a MARL framework on the basis of conventional Q-learning framework to learn the optimal policy, and to maximize the long-term expected reward. The novel strategy is also proposed to reduce the localization error. Extensive simulations demonstrate that the proposed localization method is superior to game theoretic-based distributed localization algorithm and virtual force-based distributed localization algorithm in terms of both localization accuracy and convergence speed, and is suitable for on-line localization scenarios.

关键词： distributed localization Q-learning Internet of things (IoT) Multi-agent reinforcement learning

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distributed localization using a moving beacon in wireless sensor networks

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IEEE TRANSACTIONS ON PARALLEL AND distributed SYSTEMS 2008年第5期19卷 587-600页

作者： Xiao, Bin Chen, Hekang Zhou, Shuigeng Hong Kong Polytech Univ Dept Comp Hong Kong Hong Kong Peoples R China Fudan Univ Dept Comp Sci & Engn Shanghai 200433 Peoples R China

The localization of sensor nodes is a fundamental problem in sensor networks and can be implemented using powerful and expensive beacons. Beacons, the fewer the better, can acquire their position knowledge either from GPS devices or by virtue of being manually placed. In this paper, we propose a distributed method to localization of sensor nodes using a single moving beacon, where sensor nodes compute their position estimate based on the range-free technique. Two parameters are critical to the location accuracy of sensor nodes: the radio transmission range of the beacon and how often the beacon broadcasts its position. Theoretical analysis shows that these two parameters determine the upper bound of the estimation error when the traverse route of the beacon is a straight line. We extend the position estimate when the traverse route of the beacon is randomly chosen in a real-world situation, where the radio irregularity might cause a node to miss some crucial coordinate information from the beacon. We further point out that the movement pattern of the beacon plays a pivotal role in the localization task for sensors. To minimize estimation errors, sensor nodes can carry out a variety of algorithms in accordance with the movement of the beacon. Simulation results compare variants of the distributed method in a variety of testing environments. Real experiments show that the proposed method is feasible and can estimate the location of sensor nodes accurately, given a single moving beacon.

关键词： distributed localization range-free moving beacon radio irregularity

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distributed localization of Multiagent Systems With Imperfect Channels Based on Iterative Learning

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IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS 2022年第10期69卷 10521-10529页

作者： Lv, Yunkai Zhang, Hao Huang, Chao Wang, Zhuping Tongji Univ Sch Elect & Informat Engn Shanghai 200092 Peoples R China

The real-time localization problem for a class of multiagent systems with imperfect channels under directed graphs is investigated in this article. A successive distributed localization estimation algorithm based on iterative learning is proposed to solve the localization problem of the agent with bounded communication delays. The barycentric coordinates are used to represent the relative position between agents. An estimator is proposed to inspect whether the received data packet is the latest through the iteration stamp on the packet. Meanwhile, an intermittent distributed localization algorithm is devised to handle with the random data loss of agents in real-time localization problem. The relationship between the convergence rate and the probability of the data loss is given in the sense of mathematical expectations. Both numerical simulation and Qbot-2e robot experiment are provided to verify the effectiveness and the feasibility of the aforementioned methods.

关键词： Location awareness Delays Multi-agent systems Convergence Real-time systems Heuristic algorithms distributed databases Barycentric coordinate communication delay distributed localization multiagent systems random data loss

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