Design of Customized Adaptive Radar Detectors in the CFAR Feature Plane

Abstract

The paper addresses the design of adaptive radar detectors with desired behavior, in Gaussian disturbance with unknown statistics. Specifically, based on detection probability specifications for chosen signal-to-noise ratios and steering vector mismatch levels, a methodology for the design of customized constant false alarm rate (CFAR) detectors is devised in a suitable feature plane obtained from two maximal invariant statistics. To overcome the analytical and numerical intractability of the resulting optimization problem, a novel general reducedcomplexity algorithm is developed, which is shown to be effective in providing a feasible solution (i.e., fulfilling a constraint on the probability of false alarm) while controlling the behavior under both matched and mismatched conditions, so enabling the design of fully customized adaptive CFAR detectors.

Extracting Pole Characteristics of Complex Radar Targets for the Aircraft in Resonance Region Using RMSPSO_ARMA

“…As a fundamental basis for radar target recognition in the resonance region, the characteristics of the complex resonance, namely the pole, can reveal the internal relationship between the time-domain response of the target and its inherent physical characteristics through a series of resonant frequencies and attenuation factors. Terefore, deriving the complex pole of a radar target has theoretical and practical signifcance in recognizing the unknow radar target [2,3]. Introducing the singularity expansion method (SEM) theory provided a solid foundation for the research of pole extraction methods and opened up new directions for subsequent target recognition methods [4,5].…”

“…In the proposed RMSPSO_ARMA algorithm, the aliasing of early and late responses is efectively avoided, and the problem of parameter dependence for ARMA in the actual extraction process is adequately solved. Meanwhile, this method can also be applied to cutting-edge radar detection technology and has strong foresight [2,3].…”

Information Fusion for Radar Signal Sorting with the Distributed Reconnaissance Receivers

“…These emerging radar technologies introduce more complex and diversified signal features and processing requirements, posing more intricate challenges for passive radar in reconnaissance and target identification tasks. To address these challenges, passive reconnaissance radar technology is continuously evolving and adopting enhancement techniques to improve signal detection performance, such as the application of constant false alarm rate (CFAR) properties [1]. However, in the current highdensity signal environment, traditional single-station radar reconnaissance fails to meet the reconnaissance requirements due to the influence of external factors, such as enemy interference and terrain obstruction.…”