When evaluating the effectiveness of radar antijamming techniques, the limited sample size poses a challenge. To overcome this limitation, this article proposes a signal-to-interference ratio fusion (SIRF) model that integrates multistage data. The SIRF model is based on the relationship between the signal-to-interference ratio and radar target range, considering three fluctuation models for radar cross section: Swerling I-II, Swerling III-IV, and Rayleigh. By employing the Bayesian theory and the antientropy weight method, the SIRF model enables the fusion of data collected from various stages, including mathematical simulations, hardware-in-the-loop tests, and field tests. Numerical results demonstrate that the proposed SIRF model exhibits superior consistency and robustness compared to the conventional fusion model based on the beta distribution.
A Bayesian Multistage Fusion Model for Radar Antijamming Performance Evaluation
IEEE Transactions on Aerospace and Electronic Systems ; 60 , 1 ; 729-740
01.02.2024
2926464 byte
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch