Multi-Target Detection Capability of Linear Fusion Approach Under Different Swerling Models of Target Fluctuation

Authors

  • Mohamed Bakry El_Mashade

Keywords:

adaptive detection, non-coherent integration, fluctuating targets, swerling models, target multiplicity environments

Abstract

In evolving radar systems, detection is regarded as a fundamental stage in their receiving end. Consequently, detection performance enhancement of a CFAR variant represents the basic requirement of these systems, since the CFAR strategy plays a key role in automatic detection process. Most existing CFAR variants need to estimate the background level before constructing the detection threshold. In a multi-target state, the existence of spurious targets could cause inaccurate estimation of background level. The occurrence of this effect will result in severely degrading the performance of the CFAR algorithm. Lots of research in the CFAR design have been achieved. However, the gap in the previous works is that there is no CFAR technique that can operate in all or most environmental varieties. To overcome this challenge, the linear fusion (LF) architecture, which can operate with the most environmental and target situations, has been presented.

How to Cite

Mohamed Bakry El_Mashade. (2021). Multi-Target Detection Capability of Linear Fusion Approach Under Different Swerling Models of Target Fluctuation. Global Journal of Computer Science and Technology, 21(H3), 19–42. Retrieved from https://computerresearch.org/index.php/computer/article/view/2072

Multi-Target Detection Capability of Linear Fusion Approach Under Different Swerling Models of Target Fluctuation

Published

2021-07-15