An Improved Fingerprint Algorithm with Access Point Selection and Reference Point Selection Strategies for Indoor Positioning
An Improved Fingerprint Algorithm with Access Point Selection and Reference Point Selection Strategies for Indoor Positioning
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DOI：
10.1017/s0373463319000730
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发表时间：
2020-07
影响因子：
2.4
通讯作者：
Changgeng Li;Hui Huang;Bowen Liao
中科院分区：
文献类型：
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作者：
Changgeng Li;Hui Huang;Bowen Liao
指纹定位(FP)算法由于能够提供相对理想的室内定位结果而得到了广泛的研究。然而，指纹算法的有效性依赖于指纹库的大小，这阻碍了该算法在实际应用中的广泛应用。为了减小指纹数据库的规模，提高定位精度，提出了一种结合接入点(AP)选择策略和参考点(RP)选择策略的改进指纹算法。实验结果表明，该算法可以使指纹库的存储容量减少42.%以上。此外，与FP算法、带分段特征距离的指纹算法(FP-SCD)和带RP选择策略的指纹算法(FP-RPSS)相比，该算法的平均定位误差分别降低了20.15%、10.83%和11.57%。因此，该算法在实际定位场景中有很好的应用前景。
The fingerprint positioning (FP) algorithm has been investigated extensively owing to the fact that it can provide a relatively ideal indoor positioning result. However, the effectiveness of the fingerprint algorithm relies on the size of fingerprint database, which prevents the algorithm from being widely applied in practical applications. In this paper, an improved fingerprint algorithm with access point (AP) selection strategy and reference point (RP) selection strategy is proposed to reduce the size of the fingerprint database and improve the positioning accuracy. The experimental results show that the proposed algorithm can reduce the storage size of the fingerprint database by more than 42·64%. Moreover, compared with the FP algorithm, the fingerprint algorithm with segment characteristic distance (FP-SCD) and the fingerprint algorithm with RP selection strategy (FP-RPSS), the average positioning error of the proposed algorithm is reduced by 20·15%, 10·83% and 11·57%, respectively. Therefore, the proposed algorithm has a good application in real positioning scenarios.