Heterogeneous performance assessment of new approach for partially-correlated χ2-targets adaptive detection





adaptive detection, non-coherent integration, Swerling models, fluctuating target, partially-correlated χ2-target, multi-target environment


Radars are the cornerstones of modern integrated air defense systems. The decision on the present or absence of object, ensuring non-fluctuating false alarms, represents one of its fundamental concepts. This involves the implementation of constant false alarm rate (CFAR) strategy that updates the detection threshold in accordance with the inhomogeneous observation scenario. The hardness of finding a single CFAR variant, to deal with diverse noise situations, necessitates the development of composite technique. In this regard, fusion of particular decisions of single CFAR schemes provides better final detection through appropriate fusion rules. This paper is intended with the analysis of linear fusion (LF) of CA, OS, and TM structures. The target of interest and the fallacious ones are supposed to follow χ2-model with two-degrees of freedom in their fluctuation. The closed-form expression is derived for the detection performance. Our simulation results demonstrate that the LF model exhibits robust behavior on the presence or absence of interferers. Additionally, the LF ideal performance surpasses the Neyman–Pearson (N-P) detector one, which is the yardstick of the CFAR world. Moreover, the LF strategy has the capability to hold the unchanged false alarm rate in face of the presence of interferers.


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Multi-pulse homogeneous detection performance of LF-CFAR scheme for [chi]^2-fluctuating targets with two-degrees of freedom





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