Moving Target Detection Using Fuzzy Bayesian Fusion in Multichannel SAR Framework

IF 0.3 Q4 COMPUTER SCIENCE, INFORMATION SYSTEMS
B. M., R. P
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引用次数: 0

Abstract

In this paper, a novel FBF-MTD is proposed for the detection of moving target by integrating the fuzzy concept in Bayesian fusion model. This method uses the decision fusion method that combines the matching filter, Fourier transform and the STFT. In the first step, acceleration, velocity, and RCS are simulated and the radar that returns from the target is calculated based on transmission power, distance of target, antenna gain, and RCS. Then, the FBF-MTD method combines the results of Fourier transform, short time Fourier transform, and matched filter, to produce the final decision. The performance of the proposed FBF-MTD method is analyzed with respect to the metrics, namely detection time, missed target rate, and MSE. The proposed FBF-MTD model obtained the detection time, missed target rate, and MSE values of 3.2495 sec, 0.0524, and 3344.04, respectively that show the superiority of the FBF-MTD model in MTD.
基于模糊贝叶斯融合的多通道SAR运动目标检测
在贝叶斯融合模型中引入模糊概念,提出了一种用于运动目标检测的FBF-MTD算法。该方法采用匹配滤波、傅里叶变换和STFT相结合的决策融合方法。首先对加速度、速度和RCS进行仿真,并根据发射功率、目标距离、天线增益和RCS计算从目标返回的雷达;然后,FBF-MTD方法结合傅里叶变换、短时傅里叶变换和匹配滤波器的结果,产生最终的决策。从检测时间、漏靶率和MSE等指标分析了FBF-MTD方法的性能。提出的FBF-MTD模型检测时间为3.2495秒,未靶率为0.0524秒,MSE为3344.04秒,显示了FBF-MTD模型在MTD中的优越性。
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来源期刊
International Journal of Distributed Systems and Technologies
International Journal of Distributed Systems and Technologies COMPUTER SCIENCE, INFORMATION SYSTEMS-
CiteScore
1.60
自引率
9.10%
发文量
64
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