Inhomogeneous Assessment of New Mechanism of Adaptive Detection of Partially-correlated χ2-Targets
Автор: Mohamed Bakry El-Mashede
Журнал: International Journal of Mathematical Sciences and Computing @ijmsc
Статья в выпуске: 4 vol.7, 2021 года.
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Owing to its merits in fluctuating radar targets detection, the scenario of fusion structure has rapidly become a methodology of choice. The base goal of this paper is to analyze the linear type of this methodology, which is termed as linear fusion (LF). The target of interest along with fallacious ones is assumed to be fluctuating obeying χ2-model of two-degrees of freedom in their fluctuation, with particular attention on partially-correlated target returns. Closed-form expression is derived for the detection performance of the proposed processor. The analytical results are validated with computer simulation. Our simulation results demonstrate that the LF model yields impressive detection performance in terms of detection performance and CFAR loss, in comparison with the conventional schemes in the case where the operating environment is free of or contaminated with interferers. Additionally, the LF homogeneous performance outweighs that of Neyman-Pearson (N-P) detector, which is the yardstick of the CFAR world. Moreover, the LF structure has the capability of holding the rate of false alarm fixed against the presence of interferers. The ability to obtain improved performance compared to existing models is the major contribution of this research.
Adaptive detection, post-detection integration, χ2-distribution of 2-degrees of freedom, fluctuating targets, Swerling models, partially-correlated χ2-targets, target multiplicity environments.
Короткий адрес: https://sciup.org/15018233
IDR: 15018233 | DOI: 10.5815/ijmsc.2021.04.01
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