Multi-Level Fusion Processing Algorithm for Complex Radar Signals Based on Evidence Theory
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초록
As current algorithms unable to perform effective fusion processing of unknown complex radar signals lackingdatabase, and the result is unstable, this paper presents a multi-level fusion processing algorithm for complexradar signals based on evidence theory as a solution to this problem. Specifically, the real-time database isinitially established, accompanied by similarity model based on parameter type, and then similarity matrix iscalculated. D-S evidence theory is subsequently applied to exercise fusion processing on the similarity ofparameters concerning each signal and the trust value concerning target framework of each signal in order. Thesignals are ultimately combined and perfected. The results of simulation experiment reveal that the proposedalgorithm can exert favorable effect on the fusion of unknown complex radar signals, with higher efficiency andless time, maintaining stable processing even of considerable samples.
Abstract
As current algorithms unable to perform effective fusion processing of unknown complex radar signals lackingdatabase, and the result is unstable, this paper presents a multi-level fusion processing algorithm for complexradar signals based on evidence theory as a solution to this problem. Specifically, the real-time database isinitially established, accompanied by similarity model based on parameter type, and then similarity matrix iscalculated. D-S evidence theory is subsequently applied to exercise fusion processing on the similarity ofparameters concerning each signal and the trust value concerning target framework of each signal in order. Thesignals are ultimately combined and perfected. The results of simulation experiment reveal that the proposedalgorithm can exert favorable effect on the fusion of unknown complex radar signals, with higher efficiency andless time, maintaining stable processing even of considerable samples.
참고문헌 (15)
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