The 2.5 dimensional silica fiber reinforced nitride matrix composites (2.5D SiO2f/Si3N4-BN) were prepared through the preceramic polymer impregnation pyro- lysis (PIP) method. The ablation and radar-wave transparent p...The 2.5 dimensional silica fiber reinforced nitride matrix composites (2.5D SiO2f/Si3N4-BN) were prepared through the preceramic polymer impregnation pyro- lysis (PIP) method. The ablation and radar-wave transparent performances of the composite at high temperature were evaluated under arc jet. The composition and ablation surface microstructures were studied by X-ray diffraction (XRD) and scanning electron microscope (SEM). The results show that the 2.5D SiO2f/Si3N4-BN composites have a linear ablation rate of 0.33 mm/s and high radar-wave trans- parent ratio of 98.6%. The fused layer and the matrix are protected by each other, and no fused layer accumulates on the ablation surface. The nitride composite is a high-temperature ablation resistivity and microwave transparent material.展开更多
基金the State Key Laboratory of Advanced Ceramic Fibers & Composites Foundation (Grant No. 2004js51488.0101.kg01.3) the Innovation Foundation of National University of Defense Technology for Graduate Students (Grant No. 0603)
文摘The 2.5 dimensional silica fiber reinforced nitride matrix composites (2.5D SiO2f/Si3N4-BN) were prepared through the preceramic polymer impregnation pyro- lysis (PIP) method. The ablation and radar-wave transparent performances of the composite at high temperature were evaluated under arc jet. The composition and ablation surface microstructures were studied by X-ray diffraction (XRD) and scanning electron microscope (SEM). The results show that the 2.5D SiO2f/Si3N4-BN composites have a linear ablation rate of 0.33 mm/s and high radar-wave trans- parent ratio of 98.6%. The fused layer and the matrix are protected by each other, and no fused layer accumulates on the ablation surface. The nitride composite is a high-temperature ablation resistivity and microwave transparent material.
文摘在使用毫米波雷达进行室内人员信息检测时,其信号处理阶段采用的静态杂波滤除算法有效地滤除了检测区域中包括墙壁、地面、桌椅等在内的静止目标,实现了对运动人员的检测,但同时会导致静止人员被漏检.为此提出按照径向速度把点云数据划分为动态数据和静态数据,先剔除动态数据,然后累积剩余的静态数据.在达到指定的累积帧数时,进行密度聚类,以簇的数量作为人员的数量,簇的中心坐标作为人员的位置.通过实验,验证了所提出方法的有效性,在室内办公场景下,人员数量统计平均绝对误差为0.81,人员位置估计均方根误差为0.1 m.