基片偏压对磁控溅射制备TiB_2涂层结构及性能的影响

为了提高TiB2涂层的致密性,采用磁控溅射技术,通过改变基片偏压,获得了floating,-30V,-90V三种偏压状态的涂层。利用XRD,SEM、纳米压痕仪、Vickers显微硬度仪和摩擦磨损试验机对涂层的结构和性能进行了分析。结果表明:所有制备涂层只存在六方结构TiB2相,偏压为floating状态时制备的涂层表现出疏松的柱状生长结构,硬度为15GPa。随偏压增大,涂层柱状结构变致密甚至消失,硬度和耐磨损性能都得到提高。偏压-30V提高到-90V,相对于floating状态制备的涂层,晶粒尺寸增加了一倍,达到21nm;柱状结构变致密最终消除;硬度从35.5GPa提高到61.9GPa,实现了超硬;同时耐磨损性能提高,使用摩擦副为直径6mm的Al2O3球进行干摩擦实验时,-90V制备的涂层磨损率为5.6×10-16m3/Nm,相对于-30V涂层降低了一个数量级。     

Particle filter-based real-time phase line bias estimation for GNSS-based attitude determination with common-clock receivers

Global navigation satellite system (GNSS)-based attitude determination has been widely adopted in a wide variety of terrestrial, sea, air, and space applications. Recently, the emergence of commercial multi-GNSS common-clock receivers has brought new opportunities for high-precision GNSS-based attitude determination with single-differenced (SD) model. However, the key requirement of using this approach is the accurate estimation of the troublesome line bias (LB) in real-time. In this contribution, we propose a particle filter-based real-time phase LB estimation approach that apply to SD model with single-system single-frequency observations from common-clock receiver. We first analyzed the relationship between the integer ambiguity ratio value and the phase LB. It is proved that the accuracy of a given phase LB value can be qualified by the related ambiguity resolution ratio value, and the normalized ratio value can therefore be used to represent the likelihood function of observations. Then, we presented the particle filter-based real-time phase LB estimation procedure, and assessed its performance using GPS L1/BDS B1I observations from two datasets collected with different types of common-clock receivers in terms of the accuracy and convergence time of phase LB estimation, the computation load, and the positioning and attitude determination accuracy with respect to the double-differenced (DD) model. Experimental results demonstrated that the phase LB could be accurately estimated with short convergence time (generally within 15 epochs). Moreover, compared with the classical DD approach, the particle filter-based SD approach delivers comparable positioning root-mean-square (RMS) errors in the North and East components but significantly smaller RMS errors in the Up component. Accordingly, the achievable yaw accuracy is comparable whereas the pitch accuracy is remarkably improved. The improvements of positioning accuracy in the Up component and pitch accuracy are approximately 35.7 % to 63.7 %, and 33.3 % to 63.1 %, respectively. Additionally, the single-epoch computation time with our particle filter-based SD approach is generally 0.08 s, which is obviously larger than the DD approach but could still meet the requirements of real-time applications below 10 Hz sampling.