以火星采样返回任务中火星表面上升为背景,研究了基于惯性测量单元(Inertial Measurement Unit,IMU)、嵌入式大气数据传感系统(Flush Air Data Sensing System,FADS)和无线电信标的组合导航方法。首先,在传统的IMU导航框架中加入由无线...以火星采样返回任务中火星表面上升为背景,研究了基于惯性测量单元(Inertial Measurement Unit,IMU)、嵌入式大气数据传感系统(Flush Air Data Sensing System,FADS)和无线电信标的组合导航方法。首先,在传统的IMU导航框架中加入由无线电测量获得的相对距离、速度信息,以及由FADS获取的动压、温度数据,建立了基于IMU、无线电和FADS的导航观测模型;然后,基于无迹卡尔曼滤波(Unscented Kalman Filter,UKF)技术对测量信息进行了融合,并压制了过程噪声和测量噪声,从而对上升器的状态进行了联合估计;最后,在数值仿真中,将UKF与自适应无迹卡尔曼滤波(Adaptive Unscented Kalman Filter,AUKF)技术进行了对比,在比较不同滤波器性能的同时,验证了组合导航方法的有效性。展开更多
Wireless sensor networks are envisioned to be an integral part of cyber-physical systems, yet wireless networks are inherently dynamic and come with various uncertainties. One such uncertainty is wireless communicatio...Wireless sensor networks are envisioned to be an integral part of cyber-physical systems, yet wireless networks are inherently dynamic and come with various uncertainties. One such uncertainty is wireless communication itself which assumes complex spatial and temporal dynamics. For dependable and predictable performance, therefore, link estimation has become a basic element of wireless network routing. Several approaches using broadcast beacons and/or unicast MAC feedback have been proposed in the past years, but there is still no systematic characterization of the drawbacks and sources of errors in bea- con-based link estimation in low-power wireless networks, which leads to ad hoc usage of beacons in rout- ing. Using a testbed of 98 XSM motes （an enhanced version of MICA2 motes）, we characterize the negative impact that link layer retransmission and traffic-induced interference have on the accuracy of beacon-based link estimation, and we show that data-driven link estimation and routing achieve higher event reliability （e.g. by up to 18.75%） and transmission efficiency （e.g., by up to a factor of 1.96） than beacon-based approaches These findings provide solid evidence for the necessity of data-driven link estimation and demonstrate the importance of addressing the drawbacks of beacon-based link estimation when designing protocols for low-power wireless networks of cyber-physical systems.展开更多
文摘Wireless sensor networks are envisioned to be an integral part of cyber-physical systems, yet wireless networks are inherently dynamic and come with various uncertainties. One such uncertainty is wireless communication itself which assumes complex spatial and temporal dynamics. For dependable and predictable performance, therefore, link estimation has become a basic element of wireless network routing. Several approaches using broadcast beacons and/or unicast MAC feedback have been proposed in the past years, but there is still no systematic characterization of the drawbacks and sources of errors in bea- con-based link estimation in low-power wireless networks, which leads to ad hoc usage of beacons in rout- ing. Using a testbed of 98 XSM motes （an enhanced version of MICA2 motes）, we characterize the negative impact that link layer retransmission and traffic-induced interference have on the accuracy of beacon-based link estimation, and we show that data-driven link estimation and routing achieve higher event reliability （e.g. by up to 18.75%） and transmission efficiency （e.g., by up to a factor of 1.96） than beacon-based approaches These findings provide solid evidence for the necessity of data-driven link estimation and demonstrate the importance of addressing the drawbacks of beacon-based link estimation when designing protocols for low-power wireless networks of cyber-physical systems.
