Multi-Level Fusion Processing Algorithm for Complex Radar Signals Based on Evidence Theory


Runlan Tian, Rupeng Zhao, Xiaofeng Wang, Journal of Information Processing Systems
Vol. 15, No. 5, pp. 1243-1257, Oct. 2019
10.3745/JIPS.04.0136
Keywords: Complex Radar Signal, Evidence Theory, Multi-Level Fusion, Similarity
Fulltext:

Abstract

As current algorithms unable to perform effective fusion processing of unknown complex radar signals lacking database, and the result is unstable, this paper presents a multi-level fusion processing algorithm for complex radar signals based on evidence theory as a solution to this problem. Specifically, the real-time database is initially established, accompanied by similarity model based on parameter type, and then similarity matrix is calculated. D-S evidence theory is subsequently applied to exercise fusion processing on the similarity of parameters concerning each signal and the trust value concerning target framework of each signal in order. The signals are ultimately combined and perfected. The results of simulation experiment reveal that the proposed algorithm can exert favorable effect on the fusion of unknown complex radar signals, with higher efficiency and less time, maintaining stable processing even of considerable samples.


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Cite this article
[APA Style]
Runlan Tian, Rupeng Zhao, & Xiaofeng Wang (2019). Multi-Level Fusion Processing Algorithm for Complex Radar Signals Based on Evidence Theory. Journal of Information Processing Systems, 15(5), 1243-1257. DOI: 10.3745/JIPS.04.0136.

[IEEE Style]
R. Tian, R. Zhao and X. Wang, "Multi-Level Fusion Processing Algorithm for Complex Radar Signals Based on Evidence Theory," Journal of Information Processing Systems, vol. 15, no. 5, pp. 1243-1257, 2019. DOI: 10.3745/JIPS.04.0136.

[ACM Style]
Runlan Tian, Rupeng Zhao, and Xiaofeng Wang. 2019. Multi-Level Fusion Processing Algorithm for Complex Radar Signals Based on Evidence Theory. Journal of Information Processing Systems, 15, 5, (2019), 1243-1257. DOI: 10.3745/JIPS.04.0136.