【摘要】 针对在基于WiFi信号强度RSSI进行室内定位的指纹库算法的在线匹配环节中存在的不足，该文利用基于阈值R₀动态筛选匹配的指纹点数，提出了一种增强加权k近邻算法（EWKNN）.因为阈值R₀可以动态筛选指纹库中的样本点，所以能够提高增强加权k近邻算法的适用度和高精度.仿真结果表明：在R₀设置恰当的情况下，增强加权k近邻算法的计算量与加权k近邻算法（WKNN）相当，但定位精度更高.更多还原

【Abstract】 Focused on the online matching part in fingerprint database algorithm for indoor positioning based on WiFi signal strength RSSI,the enhanced weight k-nearest method is proposed by dynamically selecting the matching fingerprint points based on the threshold R₀.The effectiveness of the enhanced weighted k-nearest neighbors algorithm（EWKNN） stems from the threshold, because the value of R₀ can dynamically filter the sample points in the fingerprint library, which is an improvement on the weight k-nearest neighbors algorithm.The result of the simulation shows that under the appropriate setting of R₀,the amount of calculation of the enhanced weight k-nearest neighbors algorithm（EWKNN） is comparable to the weighted k-nearest neighbor algorithm（WKNN）,but the positioning accuracy is higher.更多还原