Radar signal sorting is one of the crucial techniques in radar reconnaissance. However, as the electromagnetic environment increasingly complex and the density of radar pulses surges, the efficiency of clustering-based sorting algorithms is severely degraded. To better align with the streaming data characteristics of radar pulses and avoid the storage and computation of large amounts of pulse data, this article proposes a rapid radar signal sorting method based on density and Gaussian mixture model data stream clustering. First, by introducing the concepts of core clusters and outlier clusters based on a Gaussian mixture model (GMM), the proposed method achieves effective storage of online summary information for radar emitter signals with reduced space complexity. Meanwhile, by optimizing strategies for cluster evolution and incremental updates during the online phase, and by directly outputting clustering results using GMM in the offline phase, the approach achieves a significant reduction in computational load and further enhances overall efficiency. Experimental simulation results demonstrate that the proposed method excels in terms of efficiency, providing a practically valuable method for sorting radar pulse streams.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    A Rapid Radar Signal Sorting Method Based on Density and Gaussian Mixture Model Data Stream Clustering


    Contributors:
    Huo, Weibo (author) / Yu, Haoyang (author) / Zhang, Yujie (author) / Xu, Gengchen (author) / Pei, Jifang (author) / Zhang, Yin (author) / Huang, Yulin (author)

    Published in:

    Publication date :

    2025-08-01


    Size :

    3805757 byte




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English



    Support Vector Clustering and Type-Entropy Based Radar Signal Sorting Method

    Guo, Q. / Wang, C. / Li, Z. | British Library Online Contents | 2010


    Game Level Clustering and Generation using Gaussian Mixture VAEs

    Yang, Zhihan / Sarkar, Anurag / Cooper, Seth | ArXiv | 2020

    Free access

    Extracting Metro Passengers' Route Choice via AFC Data Utilizing Gaussian Mixture Clustering

    Wu, Xingtang / Dong, Hairong / Gao, Shigen et al. | IEEE | 2018


    Radar Signal Sorting and Recognition Method Based on a Novel RBF Network

    Fan, Y. / Gong, X.-b. / Zang, X.-g. et al. | British Library Online Contents | 2004