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Journal of Projectiles, Rockets, Missiles and Guidance >

2017 , Vol. 37 >Issue 3: 109 - 113

DOI: https://doi.org/10.15892/j.cnki.djzdxb.2017.03.028

CORRELATION TECHNOLOGY

Procession Feature Extraction of Ballistic Targets Based onAP-DBSCAN Clustering Algorithm

  • CHEN Rong ,
  • FENG Cunqian ,
  • WANG Yizhe ,
  • XU Dan
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  • 1 Air and Missile Defense College, Air Force Engineering University, Xi'an 710051, China
    2 Collaborative Innovation Center of Information Sensing and Understanding, Xi'an 710077, China

Received date: 2016-06-27

  Online published: 2025-05-28

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Abstract

Precession is a critical feature in the identification of ballistic targets. Aimed at cone-shaped warhead, a method to extract the precession feature of cone-shaped target, which is based on the mixed netted radars consisting of both narrowband and wideband ones, is proposed. Firstly a precession model of ballistic target is developed, and the AP clustering algorithm is introduced to cluster the echo signals on the basis of the signal intensity. Noisy points are deleted through the DBSCAN algorithm and the average values of non-noisy signals are calculated after the classification. Based on the work mentioned above, the amplitude and phase information of each scattering center in different netted radars is estimated. Then the precession parameters of ballistic targets are calculated. Simulation results validate that the precision of estimation on the precession parameters stays on high accuracy under the condition of a low signal noise ratio (SNR).

Key words： broadband radar; affinity propagation(AP); DBSCAN; procession feature extraction

Cite this article

CHEN Rong , FENG Cunqian , WANG Yizhe , XU Dan . Procession Feature Extraction of Ballistic Targets Based onAP-DBSCAN Clustering Algorithm[J]. Journal of Projectiles, Rockets, Missiles and Guidance, 2017 , 37(3) : 109 -113 . DOI: 10.15892/j.cnki.djzdxb.2017.03.028

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