The advantages of using unmanned underwater vehicles in coastal ocean studies are emphasized. Two types of representative vehicles, remotely operated vehicle (ROV) and autonomous underwater vehicle (AUV) from Universi...The advantages of using unmanned underwater vehicles in coastal ocean studies are emphasized. Two types of representative vehicles, remotely operated vehicle (ROV) and autonomous underwater vehicle (AUV) from University of South Florida, are discussed. Two individual modular sensor packages designed and tested for these platforms and field measurement results are also presented. The bottom classification and albedo package, BCAP, provides fast and accurate estimates of bottom albedos, along with other parameters such as in-water remote sensing reflectance. The real-time ocean bottom optical topographer, ROBOT, reveals high-resolution 3-dimentional bottom topography for target identification. Field data and results from recent Coastal Benthic Optical Properties field campaign, 1999 and 2000, are presented. Advantages and limitations of these vehicles and applications of modular sensor packages are compared and discussed.展开更多
文摘相比电磁波(Electromagnetic,EM),基于磁感应的通信系统更适应于非传统媒介的网络环境。但对于任意无线传感网络(Wireless Sensor Network,WSN),能量是一个有限资源。为此,提出了面向基于磁感应的非传统媒介WSN的能耗模型(Energy Consumption Model in Magnetic Induction based Non-Conventional WSN,EC-MI)。该模型针对二相相移键控(Binary Phase Shift Keying,BPSK)、16正交幅相调制(16 Quadrature Amplitude Modulation,16-QAM)和64正交幅相调制(64 Quadrature Amplitude Modulation,64-QAM)三种调制技术,建立传输单个数据包的能耗模型,并推导了能耗最小化的数据包尺寸和误比特率。再针对干燥土壤、沉积岩和海水的媒介,分析了EC-MI模型的性能。仿真结果表明,相比于沉积岩和海水域媒介,干燥土壤媒介的能耗最小。
基金support to the University of South Florida(Grants No.0014-96-1-5013 and No.0014-97-1-0006)cooperation between Ocean University of China and University of South Florida.
文摘The advantages of using unmanned underwater vehicles in coastal ocean studies are emphasized. Two types of representative vehicles, remotely operated vehicle (ROV) and autonomous underwater vehicle (AUV) from University of South Florida, are discussed. Two individual modular sensor packages designed and tested for these platforms and field measurement results are also presented. The bottom classification and albedo package, BCAP, provides fast and accurate estimates of bottom albedos, along with other parameters such as in-water remote sensing reflectance. The real-time ocean bottom optical topographer, ROBOT, reveals high-resolution 3-dimentional bottom topography for target identification. Field data and results from recent Coastal Benthic Optical Properties field campaign, 1999 and 2000, are presented. Advantages and limitations of these vehicles and applications of modular sensor packages are compared and discussed.
