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Abstract：
With the development of wireless communication technology, Ultra-Wideband (UWB) has become an important solution for indoor positioning. In complex indoor environments, the influence of non-line-of-sight (NLOS) factors leads to increased positioning errors. To improve the positioning accuracy, fuzzy iterative self-organizing data analysis clustering algorithm (ISODATA) is introduced to process a large amount of UWB data to reduce the influence of NLOS factors, and to stabilize positioning error within 2 cm, enhances the accuracy of the positioning system. To further improve the running efficiency of the algorithm, FPGA is used to accelerate the key computational part of the algorithm, compared with running on the MATLAB platform, which improves the speed about 100 times, enhances the algorithm\'s computational speed dramatically.
摘要：
随着无线通信技术的发展,超宽带(UWB)已经成为室内定位的重要解决方案。在复杂的室内环境中，非视距（NLOS）因素的影响导致定位误差增加。提高定位精度,引入模糊迭代自组织数据分析聚类算法(ISODATA)对大量UWB数据进行处理,并将定位误差稳定在2厘米以内，提高了定位系统的精度。为了进一步提高算法的运行效率,FPGA用于加速算法的关键计算部分,与在MATLAB平台上运行相比，速度提高了大约100倍，大大提高了算法的计算速度。
