基于WiFi指纹的室内定位数据处理

Proceedings of the 12th EAI International Conference on Mobile Multimedia Communications, Mobimedia 2019, 29th - 30th Jun 2019, Weihai, China Pub Date : 1900-01-01 DOI:10.4108/eai.29-6-2019.2282793

Xue-rong Cui, Mengyan Wang, Juan Li, Meiqi Ji, Jianhang Liu, Tingpei Huang, Haihua Chen

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引用次数: 0

摘要

目前，现有的位置指纹室内定位算法大多是基于原始指纹库的。指纹库的准确性将直接影响最终的定位精度。提出了一种基于偏度-峰度正态性检验和卡尔曼滤波融合的方法。实验表明，该融合算法能够有效去除RSSI (Received Signal Strength Indication)数据的突变数据和噪声波动，实现RSSI值的准确、平滑输出。

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Data Process for Indoor Positioning based on WiFi Fingerprint

Currently, most of the existing location fingerprint indoor positioning algorithms are based on the original fingerprint database. The accuracy of the fingerprint database will directly affect the final positioning accuracy. A method based on skewness-kurtosis normality test and Kalman filter fusion is proposed in this paper. Experiments shows that the fusion algorithm can effectively remove the abrupt data and noise fluctuations for the RSSI (Received Signal Strength Indication) data, and achieve accurate and smooth output of the RSSI value.

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来源期刊

Proceedings of the 12th EAI International Conference on Mobile Multimedia Communications, Mobimedia 2019, 29th - 30th Jun 2019, Weihai, China

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