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Moving Target Detection Strategy Using the Deep Learning Framework and Radar Signatures

Moving Target Detection Strategy Using the Deep Learning Framework and Radar Signatures

M. Bharat Kumar., P. Rajesh Kumar
Copyright: © 2022 |Volume: 13 |Issue: 3 |Pages: 21
ISSN: 1947-9263|EISSN: 1947-9271|EISBN13: 9781683181538|DOI: 10.4018/IJSIR.304400
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MLA

M. Bharat Kumar., and P. Rajesh Kumar. "Moving Target Detection Strategy Using the Deep Learning Framework and Radar Signatures." IJSIR vol.13, no.3 2022: pp.1-21. http://doi.org/10.4018/IJSIR.304400

APA

M. Bharat Kumar. & P. Rajesh Kumar. (2022). Moving Target Detection Strategy Using the Deep Learning Framework and Radar Signatures. International Journal of Swarm Intelligence Research (IJSIR), 13(3), 1-21. http://doi.org/10.4018/IJSIR.304400

Chicago

M. Bharat Kumar., and P. Rajesh Kumar. "Moving Target Detection Strategy Using the Deep Learning Framework and Radar Signatures," International Journal of Swarm Intelligence Research (IJSIR) 13, no.3: 1-21. http://doi.org/10.4018/IJSIR.304400

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Abstract

This paper presents deep RNN based FBF approach for the detection of moving target using the radar signatures. The FBF method is developed by the integration of fuzzy concept in the Bayesian fusion method. The FBF combines the results from the deep RNN, STFT, Fourier transform and matching filter to generate the final detection output from the received radar signal. The radar signatures are given as the input to the deep RNN for the detection of the target. Finally, the FBF combines the results from the deep RNN, STFT, Fourier transform and the matched filter to obtain the final decision regarding the detected target. The performance of the proposed deep RNN based FBF method is evaluated based on the metrics, like detection time, MSE and Missing target by varying the number of targets, antenna turn velocity, pulse repetition level, and the number of iterations. The proposed deep RNN based FBF method obtained a minimal detection time of 2.9551s, minimal MSE of 2683.80 and minimal Missing target rate of 0.0897, respectively.

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