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Aiming at the problems of uneven distribution of sensing nodes and abnormal values in monitoring data, an urban environment electromagnetic spectrum map construction method was proposed by combining density-based spatial clustering of applications with noise(DBSCAN)and inverse distance weighting(IDW)algorithm. Firstly, DBSCAN was used to reduce the influence of extreme values, and separate the core points, boundary points and noise points. The local density of each core point was used as weight to calculate the weighted center point of the cluster. Secondly, IDW was used to interpolate the weighted center point of the cluster, by which the number of data points needed to be interpolated could be significantly reduced and the electromagnetic spectrum map would be more accurate. Simulation results showed that compared with the IDW algorithm and the VIDW algorithm, the mean absolute error and the normalized mean square error of the electromagnetic spectrum map reconstructed by the proposed algorithm can be reduced by more than 10% and 23% respectively.
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Basic Information:
DOI：10.20189/j.cnki.cn/61-1527/e.2024.04.012
China Classification Code:TN011
Citation Information:
[1]XIE Jiawei,YU Zhiyong,LYU Dian ,et al.Construction of Electromagnetic Spectrum Map for Urban Environment Based on DBSCAN-IDW Algorithm[J].Journal of Rocket Force University of Engineering,2024,38(04):93-97+107.DOI:10.20189/j.cnki.cn/61-1527/e.2024.04.012.
2024-08-15
2024-08-15