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Iterative Particle Reduction Methods and Systems for Localization and Pattern Recognition

机译:用于定位和模式识别的迭代粒子约简方法和系统

摘要

Systems and methods using iterative particle reduction for localization and pattern recognition are disclosed. In one embodiment, a method for localization of a plurality of sensor nodes includes establishing a set of particles representing candidate positions for the plurality of sensor nodes; iteratively reducing the set of particles using a plurality of particle reduction iterations, wherein each particle reduction iteration eliminates at least some particles based on at least one constraint and a set of remaining particles from a prior iteration; and after performing the plurality of particle reduction iterations, determining a set of probable locations of the plurality of sensor nodes based on a final set of particles.
机译:公开了使用迭代粒子减少进行定位和模式识别的系统和方法。在一个实施例中,一种用于对多个传感器节点进行定位的方法包括:建立代表多个传感器节点的候选位置的一组粒子;使用多个粒子减少迭代来迭代地减少粒子集合,其中每个粒子减少迭代基于至少一个约束和来自先前迭代的一组剩余粒子来消除至少一些粒子;在执行所述多个粒子减少迭代之后,基于最终的粒子集合来确定所述多个传感器节点的可能位置的集合。

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