检索结果-内蒙古大学图书馆

IEEE International Conference on Digital Signal Processing (DSP)

作者： Zhu, Yanping Jiang, Aimin Kwan, Hon Keung He, Keren Changzhou Univ Sch Informat Sci & Engn Changzhou Peoples R China Hohai Univ Coll Internet Things Engn Changzhou Peoples R China Univ Windsor Dept Elect & Comp Engn Windsor ON Canada

ISBN: (纸本)9781479980581

A distributed sensor network localization algorithm is presented in this paper. During the localization procedure, each sensor estimates its own coordinate using a local multidimensional scaling (MDS) algorithm. In contrast to the classical MDS algorithm adopting the centralized processing, all the neighbors of each sensor are considered as anchor nodes in the local MDS algorithm. Furthermore, each sensor's coordinate could be estimated by its neighbors based on their respective knowledge. These local estimates are then collected by corresponding sensors and used in a combination step to finally determine sensors' coordinates. In this way, each sensor's knowledge could be diffused and shared in the network. Simulation results show that, compared to the classical MDS algorithm, the proposed algorithm is more robust to measurement noise. Moreover, when sensors are sparsely connected, the distributed MDS algorithm performs better than the centralized version of the MDS algorithm.

关键词： Diffusion scheme distributed localization multidimensional scaling (MDS) algorithm sensor network

来源：评论

学校读者我要写书评

暂无评论

Efficient Estimator for distributed RSS-based localization in Wireless Sensor Networks 11

Efficient Estimator for Distributed RSS-based Localization i...

引用

11th IEEE International Wireless Communications and Mobile Computing Conference (IEEE IWCMC)

作者： Tomic, Slavisa Beko, Marko Dinis, Rui Lipovac, Vlatko ISR IST Lisbon Portugal Univ Lusofona Humanidades & Tecnol Lisbon Portugal DEE FCT UNL Caparica Portugal CTS UNINOVA Campus FCT UNL Caparica Portugal Inst Telecomunicacoes Lisbon Portugal UNIDU Dept Elect Engn & Comp Dubrovnik Croatia

ISBN: (纸本)9781479953448

We address the received signal strength (RSS) based target localization problem in large-scale cooperative wireless sensor networks (WSNs). Using the noisy RSS measurements, we formulate the localization problem based on the maximum likelihood (ML) criterion. Although MLbased solutions have asymptotically optimal performance, the derived localization problem is non-convex. To overcome this difficulty, we propose a convex relaxation leading to second-order cone programming (SOCP) estimator, which can be solved efficiently by interior-point algorithms. Moreover, we investigate the case where target nodes limit the number of cooperating nodes by selecting only those neighbors with the highest RSS. This simple procedure can reduce the energy consumption of an algorithm in both communication and computation phase. Our simulation results show that the proposed approach outperforms significantly the existing ones in terms of the estimation accuracy and convergence. Furthermore, the new approach does not suffer significant performance degradation when the number of cooperating nodes is reduced.

关键词： Wireless localization wireless sensor network (WSN) received signal strength (RSS) second-order cone programming problem (SOCP) cooperative localization distributed localization

来源：评论

学校读者我要写书评

暂无评论

Sensor Network localization Via distributed Randomized Gradient Descent

Sensor Network Localization Via Distributed Randomized Gradi...

引用

IEEE Military Communications Conference

作者： Naraghi-Pour, Mort Rojas, Gustavo Chacon Louisiana State Univ Sch Elect Engn & Comp Sci Div Elect & Comp Engn Baton Rouge LA 70803 USA

ISBN: (纸本)9780769551241

A novel algorithm referred to as distributed randomized gradient descent (DRGD), is presented for the localization of nodes in a wireless sensor network. It is proven that, in the case of noise-free measurements, the algorithm converges and provides the true location of the nodes. In the case of noisy distance measurements the convergence properties of the algorithm are discussed and an error bound on the location estimation error is obtained. In contrast to several recently proposed methods, DRGD converges for only a few anchor nodes and the blind nodes do not need to be contained in the convex hull of the anchor nodes. Through extensive simulations and for several networks with and without distance errors, the performance of the proposed algorithm is evaluated and compared with three other recently proposed algorithms, namely the relaxation-based second order cone programming (SOCP), the simulated annealing (SA), and the semi-definite programing (SDP). Similar to DRGD, SOCP and SA are distributed algorithms, whereas SDP is centralized. The results show that the proposed algorithm successfully localizes the nodes in all the cases whereas, in most cases where only a few anchors are used, SOCP and SA fail.

关键词： distributed localization wireless sensor network randomized gradient descent basin of attraction

来源：评论

学校读者我要写书评

暂无评论

distributed cognition based localization for AR-aided collaborative assembly in industrial environments

引用

ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING 2022年 75卷

作者： Fang, Wei Fan, Wei Ji, Wei Han, Lei Xu, Shuhong Zheng, Lianyu Wang, Lihui Beijing Univ Posts & Telecommun Sch Modern Post Sch Automat Beijing Peoples R China Beihang Univ Sch Mech Engn & Automat Beijing Peoples R China Sandv Coromant Dept Digital Machining Stockholm Sweden COMAC Beijing Aircraft Technol Res Inst Beijing Peoples R China KTH Royal Inst Technol Dept Prod Engn Stockholm Sweden

The existing (augmented reality) AR-aided assembly is highly associated with AR devices, which mainly provides guidance for one operator, and it is hard to share augmented assembly instructions for large-scale products which require multiple operators working together. To address this problem, the paper proposes a distributed cognition based localization method for AR-aided collaborative assembly. Firstly, a scene cognition using multi-view acquisition about industrial environments is performed with incremental modeling in advance, providing the foundation for the subsequent pose estimate of multi-AR clients. Then, based on feature extracting and matching against the pre-built shop floor model, a pose recovery of AR-aided system is derived from different views of AR operators in a global coordinate system, followed by a distributed motion tracking with the complementary features of visual and inertial data, resulting in a co-located collaborative AR instruction for assembly. Finally, experiments are carried out to validate the proposed method, and experimental results illustrate that the proposed method can achieve distributed cognition-based localization accurately and robustly. Therefore, shared visual communications among multiple operators are synchronized, and assembly status is aware by all the operators.

关键词： distributed localization Augmented reality Collaborative AR assembly Scene cognition

来源：评论

学校读者我要写书评

暂无评论

distributed RSS-Based localization in Wireless Sensor Networks Based on Second-Order Cone Programming

引用

SENSORS 2014年第10期14卷 18410-18432页

作者： Tomic, Slavisa Beko, Marko Dinis, Rui IST ISR P-1049001 Lisbon Portugal Univ Lusofona Humanidades & Tecnol P-1749024 Lisbon Portugal Univ Nova Lisboa P-2829516 Monte De Caparica Caparica Portugal Inst Telecomunicacoes P-1049001 Lisbon Portugal Univ Nova Lisboa DEE FCT P-2829516 Monte De Caparica Portugal

In this paper, we propose a new approach based on convex optimization to address the received signal strength (RSS)-based cooperative localization problem in wireless sensor networks (WSNs). By using iterative procedures and measurements between two adjacent nodes in the network exclusively, each target node determines its own position locally. The localization problem is formulated using the maximum likelihood (ML) criterion, since ML-based solutions have the property of being asymptotically efficient. To overcome the non-convexity of the ML optimization problem, we employ the appropriate convex relaxation technique leading to second-order cone programming (SOCP). Additionally, a simple heuristic approach for improving the convergence of the proposed scheme for the case when the transmit power is known is introduced. Furthermore, we provide details about the computational complexity and energy consumption of the considered approaches. Our simulation results show that the proposed approach outperforms the existing ones in terms of the estimation accuracy for more than 1 : 5 m. Moreover, the new approach requires a lower number of iterations to converge, and consequently, it is likely to preserve energy in all presented scenarios, in comparison to the state-of-the-art approaches.

关键词： wireless localization wireless sensor network (WSN) received signal strength (RSS) second-order cone programming (SOCP) problem cooperative localization distributed localization

来源：评论

学校读者我要写书评

暂无评论

distributed Joint Cooperative Self-localization and Target Tracking Algorithm for Mobile Networks

引用

SENSORS 2019年第18期19卷 3829页

作者： Zhang, Junjie Cui, Jianhua Wang, Zhongyong Ding, Yingqiang Xia, Yujie Luoyang Normal Univ Sch Phys & Elect Informat Luoyang 471934 Peoples R China Zhengzhou Univ Sch Informat Engn Zhengzhou 450001 Henan Peoples R China

Location information is a key issue for applications of the Internet of Things. In this paper, we focus on mobile wireless networks with moving agents and targets. The positioning process is divided into two phases based on the factor graph, i.e., a prediction phase and a joint self-location and tracking phase. In the prediction phase, we develop an adaptive prediction model by exploiting the correlation of trajectories within a short period to formulate the prediction message. In the joint positioning phase, agents calculate the cooperative messages according to variational message passing and locate themselves. Simultaneously, the average consensus algorithm is employed to realize distributed target tracking. The simulation results show that the proposed prediction model is adaptive to the random movement of nodes. The performance of the proposed joint self-location and tracking algorithm is better than the separate cooperative self-localization and tracking algorithms.

关键词： mobile networks distributed localization variational message passing average consensus prediction model

来源：评论

学校读者我要写书评

暂无评论

A Bias Compensation Method for distributed Moving Source localization Using TDOA and FDOA with Sensor Location Errors

引用

SENSORS 2018年第11期18卷 3747页

作者： Liu, Zhixin Wang, Rui Zhao, Yongjun Natl Digital Switching Syst Engn & Technol Res Ct Zhengzhou 450002 Henan Peoples R China Informat Engn Univ Inst Surveying & Mapping Zhengzhou 450002 Henan Peoples R China

Current bias compensation methods for distributed localization consider the time difference of arrival (TDOA) and frequency difference of arrival (FDOA) measurements noise, but ignore the negative influence by the sensor location uncertainties on source localization accuracy. Therefore, a new bias compensation method for distributed localization is proposed to improve the localization accuracy in this paper. This paper derives the theoretical bias of maximum likelihood estimation when the sensor location errors and positioning measurements noise both exist. Using the rough estimate result by MLE to subtract the theoretical bias can obtain a more accurate source location estimation. Theoretical analysis and simulation results indicate that the theoretical bias derived in this paper matches well with the actual bias in moderate noise level so that it can prove the correctness of the theoretical derivation. Furthermore, after bias compensation, the estimate accuracy of the proposed method achieves a certain improvement compared with existing methods.

关键词： distributed localization bias compensation sensor location errors time difference of arrival frequency difference of arrival

来源：评论

学校读者我要写书评

暂无评论

Efficient Estimator for distributed RSS-based localization in Wireless Sensor Networks

Efficient Estimator for Distributed RSS-based Localization i...

引用

International Wireless Communications and Mobile Computing Conference

作者： Slavisa Tomic Marko Beko Rui Dinis Vlatko Lipovac ISR/IST Universidade Lusofona de Humanidades e Tecnologias DEE/FCT/UNL Dpt. of Electrical Engineering and Computing UNIDU

ISBN: (纸本)9781479953455

We address the received signal strength (RSS) based target localization problem in large-scale cooperative wireless sensor networks (WSNs). Using the noisy RSS measurements, we formulate the localization problem based on the maximum likelihood (ML) criterion. Although ML-based solutions have asymptotically optimal performance, the derived localization problem is non-convex. To over-come this difficulty, we propose a convex relaxation leading to second-order cone programming (SOCP) estimator, which can be solved efficiently by interior-point algorithms. Moreover, we investigate the case where target nodes limit the number of cooperating nodes by selecting only those neighbors with the highest RSS. This simple procedure can reduce the energy consumption of an algorithm in both communication and computation phase. Our simulation results show that the proposed approach outperforms significantly the existing ones in terms of the estimation accuracy and convergence. Furthermore, the new approach does not suffer significant performance degradation when the number of cooperating nodes is reduced.

关键词： Wireless localization Wireless sensor network (WSN) Received signal strength (RSS) Second-order cone programming problem (SOCP) Cooperative localization distributed localization

来源：评论

学校读者我要写书评

暂无评论

Understanding Node Localizability in Barycentric Linear localization

引用

IEEE-ACM TRANSACTIONS ON NETWORKING 2023年第3期31卷 1353-1368页

作者： Ping, Haodi Wang, Yongcai Li, Deying Chen, Wenping Renmin Univ China Dept Comp Sci Beijing 100872 Peoples R China

The barycentric linear localization (BLL) methods provide a lightweight, distributed way to calculate locations for resource-limited IoT devices. A crucial requirement for BLL is that the nodes participating in the iterative location propagation are localizable. Otherwise, the unlocalizable nodes will continuously pose error information in the location propagation process, making even the theoretically localizable nodes converge to the wrong locations. However, the research on node localizability in BLL is much lacked, greatly limiting the application scope of BLL. In specific, BLL node localizability is detected on a generated graph G(A). For any node, its neighbors appear in G(A) only when the neighbors can form triangle(s), so that G(A) is much sparser than the original G. Thus, the node localizability condition in BLL is harder to be satisfied than that in traditional localization methods. Moreover, the distributed algorithm to detect BLL localizable nodes is still open. This paper thoroughly investigates the node localizability conditions and distributed localizable node detection algorithms in BLL. At first, an efficient and fully distributed Negative Edge Inference (NEI) algorithm is proposed for each node to infer implicit edges in its neighborhood. NEI strengthens the distance graph by revealing more distance constraints so that enables more neighboring triangles. Then a new sufficient condition, i.e., the recursive three disjoint path condition (Recursive-3DP) on the strengthened distance graph is proposed to identify BLL localizable nodes much more accurately. Secondly, a distributed Path Extension and Pruning (PEP) algorithm is proposed for distributed localizable node detection. PEP is proved to detect all the theoretically Recursive-3DP nodes in the strengthened distance graph. A Fast-PEP algorithm is further proposed, which misses very limited Recursive-3DP nodes while bringing significant improvement in efficiency. PEP and Fast-PEP guarantee to ident

关键词： Barycentric coordinate distributed localization node localizability condition distributed localizability detection

来源：评论

学校读者我要写书评

暂无评论

localization Technique Considering Position Uncertainty of Reference Nodes in Wireless Sensor Networks

引用

IEEE SENSORS JOURNAL 2018年第3期18卷 1324-1332页

作者： Kim, Youngjoon Lee, Byeongho So, Hyoungmin Kim, Seong-Cheol Seoul Natl Univ Dept Elect Engn Seoul 08826 South Korea Seoul Natl Univ INMC Seoul 08826 South Korea Agcy Def Dev Daejeon 34060 South Korea

This paper proposes a distributed localization algorithm in wireless sensor networks. The algorithm considers the position uncertainty of reference nodes, which have been ignored in the past research, in which imperfect position information of reference nodes intensifies the error accumulation phenomenon. The algorithm calculates position uncertainty by the dilution of precision and presents a balance point between range errors and position errors by applying the modified spring mass method. We verify the feasibility of the proposed algorithm by changing multiple parameters under various circumstances. The result proves that the overall performance of localization is enhanced by considering the position uncertainty.

关键词： Position uncertainty spring mass method dilution of precision distributed localization wireless sensor networks

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：