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Wireless Localization Based on RSSI Fingerprint Feature Vector

机译:基于RSSI指纹特征向量的无线定位

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RSSI wireless signal is a reference information that is widely used in indoor positioning. However, due to the wireless multipath influence, the value of the received RSSI will have large fluctuations and cause large distance error when RSSI is fitted to distance. But experimental data showed that, being affected by the combined factors of the environment, the received RSSI feature vector which is formed by lots of RSSI values from different APs is a certain stability. Therefore, the paper proposed RSSI-based fingerprint feature vector algorithm which divides location area into grids, and mobile devices are localized through the similarity matching between the real-time RSSI feature vector and RSSI fingerprint database feature vectors. Test shows that the algorithm can achieve positioning accuracy up to 2–4 meters in a typical indoor environment.
机译:RSSI无线信号是在室内定位中广泛使用的参考信息。然而,由于无线多径的影响,当将RSSI拟合到距离时,接收到的RSSI的值将具有较大的波动并导致较大的距离误差。但是实验数据表明,受环境综合因素的影响,由来自不同接入点的大量RSSI值构成的接收RSSI特征向量具有一定的稳定性。因此,本文提出了一种基于RSSI的指纹特征向量算法,该算法将位置区域划分为网格,并通过实时RSSI特征向量与RSSI指纹数据库特征向量之间的相似性匹配来定位移动设备。测试表明,该算法在典型的室内环境下可以达到2-4米的定位精度。

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