2015Unpublished venueRequires access

Method against drfm dense false target jamming based on jamming recognization

Fengbo Chen Fengbo Chen, Rongfeng Li Rongfeng Li, Liming Ding, L. Liu, Lingyan Dai Lingyan Dai, Gang Deng

Open publisher page 12 citations

Abstract

In this paper, to suppress the digital radio frequency memory (DRFM) false target jamming, we introduce a jamming recognition-based method. The method first extracts mixed target and jamming samples, then computes adaptive weights by subsections of mixed samples, finally recognizes the jamming samples according to the adaptive power residue (APR) criterion. Numerical examples are provided which verify the effectiveness of the proposed method.

About this research paper

What this paper is about

In this paper, to suppress the digital radio frequency memory (DRFM) false target jamming, we introduce a jamming recognition-based method. The method first extracts mixed target and jamming samples, then computes adaptive weights by subsections of mixed samples, finally recognizes the jamming samples according to the adaptive power residue (APR) criterion. Numerical examples are provided which verify the effectiveness of the proposed method.

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OpenAlex reports 12 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Method / approach

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Available abstract

In this paper, to suppress the digital radio frequency memory (DRFM) false target jamming, we introduce a jamming recognition-based method. The method first extracts mixed target and jamming samples, then computes adaptive weights by subsections of mixed samples, finally recognizes the jamming samples according to the adaptive power residue (APR) criterion. Numerical examples are provided which verify the effectiveness of the proposed method.

Key concepts: Jamming, Radar jamming and deception, Digital radio frequency memory, Computer science, Algorithm, Radar, Telecommunications, Pulse-Doppler radar

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