The probabilistic data association algorithm is applied in the spatial domain multi resolution frame and target tracking is implemented at the coarse resolution level.
这个算法在空间多分辨率框架下应用概率数据互联算法，在粗分辨率上实现模糊目标跟踪。
Based on the unified data modeling, this resolution realizes the uniform request service to distributed heterogeneous spatial data by metadata and multi-database system.
该解决方案通过建立统一的数据模型，使用元数据与多数据库系统实现了对分布的异构的空间数据的统一访问请求服务。
Aiming at single sensor's limitation on spectrum and spatial resolution, this paper USES the technology of multi-sensor fusion, which furthest obtains the information description of target scene.
针对单一传感器在光谱、空间分辨率等方面存在的局限性，通过多传感器融合技术，最大限度地获取对目标场景的信息描述。
Currently, traditional spatial data model with the inherent limitations can not fully satisfy the scope of the global multi-resolution massive data dynamic management requirements.
当前，传统空间数据组织与模型的内在局限性已经不能完全满足大范围甚至全球多分辨率海量数据动态管理的要求。
Combining coherent technology with incoherent technology, the method can increase the number of image pixels, and therefore improve the spatial resolution of PMMW multi-beam imaging.
该方法将相干和非相干技术进行有效融合，能增加PMMW多波束成像像素，提高成像分辨率。
Combining coherent technology with incoherent technology, the method can increase the number of image pixels, and therefore improve the spatial resolution of PMMW multi-beam imaging.
该方法将相干和非相干技术进行有效融合，能增加PMMW多波束成像像素，提高成像分辨率。
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