Underwater Acoustic Sensor Network(UASN) has attracted significant attention because of its great influence on ocean exploration and monitoring. On account of the unique characteristics of underwater environment, loca...Underwater Acoustic Sensor Network(UASN) has attracted significant attention because of its great influence on ocean exploration and monitoring. On account of the unique characteristics of underwater environment, localization, as one of the fundamental tasks in UASNs, is a more challenging work than in terrestrial sensor networks. A survey of the ranging algorithms and the network architectures varied with different applications in UASNs is provided in this paper. Algorithms used to estimate the coordinates of the UASNs nodes are classified into two categories: rangebased and range-free. In addition, we analyze the architectures of UASNs based on different applications, and compare their performances from the aspects of communication cost, accuracy, coverage and so on. Open research issues which would affect the accuracy of localization are also discussed, including MAC protocols, sound speed and time synchronization.展开更多
The problem of phase retrieval is revisited and studied from a fresh perspective.In particular,we establish a connection between the phase retrieval problem and the sensor network localization problem,which allows us ...The problem of phase retrieval is revisited and studied from a fresh perspective.In particular,we establish a connection between the phase retrieval problem and the sensor network localization problem,which allows us to utilize the vast theoretical and algorithmic literature on the latter to tackle the former.Leveraging this connection,we develop a two-stage algorithm for phase retrieval that can provably recover the desired signal.In both sparse and dense settings,our proposed algorithm improves upon prior approaches simultaneously in the number of required measurements for recovery and the reconstruction time.We present numerical results to corroborate our theory and to demonstrate the efficiency of the proposed algorithm.As a side result,we propose a new form of phase retrieval problem and connect it to the complex rigidity theory proposed by Gortler and Thurston(in:Connelly R,Ivic Weiss A,Whiteley W(eds)Rigidity and symmetry,Springer,New York,pp 131–154,2014).展开更多
Underwater sensor network can achieve the unmanned environmental monitoring and military monitoring missions.Underwater acoustic sensor node cannot rely on the GPS to position itself,and the traditional indirect posit...Underwater sensor network can achieve the unmanned environmental monitoring and military monitoring missions.Underwater acoustic sensor node cannot rely on the GPS to position itself,and the traditional indirect positioning methods used in Ad Hoc networks are not fully applicable to the localization of underwater acoustic sensor networks.In this paper,we introduce an improved underwater acoustic network localization algorithm.The algorithm processes the raw data before localization calculation to enhance the tolerance of random noise.We reduce the redundancy of the calculation results by using a more accurate basic algorithm and an adjusted calculation strategy.The improved algorithm is more suitable for the underwater acoustic sensor network positioning.展开更多
基金supported by National Natural Science Foundation of China under Grants 61001067,61371093and 61172105Natural Science Foundation of Zhejiang Prov.China under Grants LY13D060001
文摘Underwater Acoustic Sensor Network(UASN) has attracted significant attention because of its great influence on ocean exploration and monitoring. On account of the unique characteristics of underwater environment, localization, as one of the fundamental tasks in UASNs, is a more challenging work than in terrestrial sensor networks. A survey of the ranging algorithms and the network architectures varied with different applications in UASNs is provided in this paper. Algorithms used to estimate the coordinates of the UASNs nodes are classified into two categories: rangebased and range-free. In addition, we analyze the architectures of UASNs based on different applications, and compare their performances from the aspects of communication cost, accuracy, coverage and so on. Open research issues which would affect the accuracy of localization are also discussed, including MAC protocols, sound speed and time synchronization.
文摘The problem of phase retrieval is revisited and studied from a fresh perspective.In particular,we establish a connection between the phase retrieval problem and the sensor network localization problem,which allows us to utilize the vast theoretical and algorithmic literature on the latter to tackle the former.Leveraging this connection,we develop a two-stage algorithm for phase retrieval that can provably recover the desired signal.In both sparse and dense settings,our proposed algorithm improves upon prior approaches simultaneously in the number of required measurements for recovery and the reconstruction time.We present numerical results to corroborate our theory and to demonstrate the efficiency of the proposed algorithm.As a side result,we propose a new form of phase retrieval problem and connect it to the complex rigidity theory proposed by Gortler and Thurston(in:Connelly R,Ivic Weiss A,Whiteley W(eds)Rigidity and symmetry,Springer,New York,pp 131–154,2014).
基金performed in the Project "The Research of Cluster Structure Based Underwater Acoustic Communication Network Topology Algorithm"supported by National Natural Science Foundation of China(No.61101164)
文摘Underwater sensor network can achieve the unmanned environmental monitoring and military monitoring missions.Underwater acoustic sensor node cannot rely on the GPS to position itself,and the traditional indirect positioning methods used in Ad Hoc networks are not fully applicable to the localization of underwater acoustic sensor networks.In this paper,we introduce an improved underwater acoustic network localization algorithm.The algorithm processes the raw data before localization calculation to enhance the tolerance of random noise.We reduce the redundancy of the calculation results by using a more accurate basic algorithm and an adjusted calculation strategy.The improved algorithm is more suitable for the underwater acoustic sensor network positioning.
