Formation control is essential for an underwater mobile sensing network(UMSN) ,and an ad hoc network which wirelessly connects underwater vehicles of sensing and/or observing types via acoustic communications,to fulfi...Formation control is essential for an underwater mobile sensing network(UMSN) ,and an ad hoc network which wirelessly connects underwater vehicles of sensing and/or observing types via acoustic communications,to fulfill mobile sensing tasks.The problem of formation control for a UMSN with varying topology is studied in this paper.The methodology of synthesizing distributed formation controller which stabilizes a UMSN with varying topology is proposed on the basis of the stability analysis of linear time-varying systems.展开更多
Comprised by a swarm of acoustically linked and cooperative autonomous underwater vehicles(AUVs) with onboard sensors,an underwater mobile sensing network(UMSN) will be a complementary means to fixed observatory netwo...Comprised by a swarm of acoustically linked and cooperative autonomous underwater vehicles(AUVs) with onboard sensors,an underwater mobile sensing network(UMSN) will be a complementary means to fixed observatory networks,e.g.seafloor observatory networks and moored buoy arrays.It has obvious advantages over a single large AUV in higher efficiency due to parallel observation,stronger robustness to vehicle failures and lower cost.Although an UMSN can be viewed as a counterpart of wireless mobile sensing networks for air and terrestrial applications,it is much more challenging due to poor performance of underwater acoustic communication, poor performance of underwater positioning and high degree of uncertainty in vehicle dynamics and underwater environment.In order to verify key technologies involved in an UMSN,e.g.cooperation of multi-AUVs based on acoustic communication,a low cost testbed has been developed for experimental study.The design of both hardware and software is introduced.Also the results of a functional test for verification of the effectiveness of the testbed are presented.展开更多
Underwater mobile sensor networks(UMSNs) with free-floating sensors are more suitable for understanding the immense underwater environment. Target tracking, whose performance depends on sensor localization accuracy, i...Underwater mobile sensor networks(UMSNs) with free-floating sensors are more suitable for understanding the immense underwater environment. Target tracking, whose performance depends on sensor localization accuracy, is one of the broad applications of UMSNs. However, in UMSNs, sensors move with environmental forces,so their positions change continuously, which poses a challenge on the accuracy of sensor localization and target tracking. We propose a high-accuracy localization with mobility prediction(HLMP) algorithm to acquire relatively accurate sensor location estimates. The HLMP algorithm exploits sensor mobility characteristics and the multistep Levinson-Durbin algorithm to predict future positions. Furthermore, we present a simultaneous localization and target tracking(SLAT) algorithm to update sensor locations based on measurements during the process of target tracking. Simulation results demonstrate that the HLMP algorithm can improve localization accuracy significantly with low energy consumption and that the SLAT algorithm can further decrease the sensor localization error. In addition, results prove that a better localization accuracy will synchronously improve the target tracking performance.展开更多
基金the National High Technology Research and Development Program (863) of China (No.2006AA09Z233)
文摘Formation control is essential for an underwater mobile sensing network(UMSN) ,and an ad hoc network which wirelessly connects underwater vehicles of sensing and/or observing types via acoustic communications,to fulfill mobile sensing tasks.The problem of formation control for a UMSN with varying topology is studied in this paper.The methodology of synthesizing distributed formation controller which stabilizes a UMSN with varying topology is proposed on the basis of the stability analysis of linear time-varying systems.
基金the National High Technology Research and Development Program(863) of China (No.2006AA09Z233)
文摘Comprised by a swarm of acoustically linked and cooperative autonomous underwater vehicles(AUVs) with onboard sensors,an underwater mobile sensing network(UMSN) will be a complementary means to fixed observatory networks,e.g.seafloor observatory networks and moored buoy arrays.It has obvious advantages over a single large AUV in higher efficiency due to parallel observation,stronger robustness to vehicle failures and lower cost.Although an UMSN can be viewed as a counterpart of wireless mobile sensing networks for air and terrestrial applications,it is much more challenging due to poor performance of underwater acoustic communication, poor performance of underwater positioning and high degree of uncertainty in vehicle dynamics and underwater environment.In order to verify key technologies involved in an UMSN,e.g.cooperation of multi-AUVs based on acoustic communication,a low cost testbed has been developed for experimental study.The design of both hardware and software is introduced.Also the results of a functional test for verification of the effectiveness of the testbed are presented.
基金Project supported by the NSFC-Zhejiang Joint Fund for the Integration of Industrialization and Informatization(No.U1609204)the National Natural Science Foundation of China(Nos.61531015 and 61673345)the Key Research and Development Program of Zhejiang Province,China(No.2018C03030)
文摘Underwater mobile sensor networks(UMSNs) with free-floating sensors are more suitable for understanding the immense underwater environment. Target tracking, whose performance depends on sensor localization accuracy, is one of the broad applications of UMSNs. However, in UMSNs, sensors move with environmental forces,so their positions change continuously, which poses a challenge on the accuracy of sensor localization and target tracking. We propose a high-accuracy localization with mobility prediction(HLMP) algorithm to acquire relatively accurate sensor location estimates. The HLMP algorithm exploits sensor mobility characteristics and the multistep Levinson-Durbin algorithm to predict future positions. Furthermore, we present a simultaneous localization and target tracking(SLAT) algorithm to update sensor locations based on measurements during the process of target tracking. Simulation results demonstrate that the HLMP algorithm can improve localization accuracy significantly with low energy consumption and that the SLAT algorithm can further decrease the sensor localization error. In addition, results prove that a better localization accuracy will synchronously improve the target tracking performance.
