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- Title
Multisource Target Data Fusion Tracking Method for Heterogeneous Network Based on Data Mining.
- Authors
Guo, Hongyan; Li, Xintao
- Abstract
This research is on heterogeneous network fusion method of multisource target data based on data mining. Firstly, it is a distributed storage structure model for building heterogeneous network multisource target data. Then, using the phase space reconstruction method, a grid distribution structure model for data fusion tracking is constructed, and realize visual scheduling and automatic monitoring of multisource target data. Finally, according to the feature extraction results, analyze the statistical characteristics of multisource target data in heterogeneous networks, combined with the fuzzy tomographic analysis method, multilevel fusion, and adaptive mining of multisource target data, extract the associated feature quantities in it, and realize the fusion tracking of data. The simulation results show that, in relatively simple heterogeneous networks, the feature mining error of the proposed method is nearly 2.11% lower than the two traditional methods. In relatively complex heterogeneous networks, the feature mining error of the proposed method is nearly 6.48% lower than the two traditional methods. It can be seen that this method has better adaptability for fusion tracking of heterogeneous network multisource target data, the anti-interference ability is strong, and the tracking accuracy in the data fusion tracking process is also improved.
- Subjects
MULTISENSOR data fusion; DATA mining; PHASE space; FEATURE extraction; TRACKING radar; ARTIFICIAL satellite tracking; ADAPTIVE fuzzy control
- Publication
Wireless Communications & Mobile Computing, 2022, p1
- ISSN
1530-8669
- Publication type
Article
- DOI
10.1155/2022/9291319