Cargando…
Novel Approach for the Recognition and Prediction of Multi-Function Radar Behaviours Based on Predictive State Representations
The extensive applications of multi-function radars (MFRs) have presented a great challenge to the technologies of radar countermeasures (RCMs) and electronic intelligence (ELINT). The recently proposed cognitive electronic warfare (CEW) provides a good solution, whose crux is to perceive present an...
Autores principales: | Ou, Jian, Chen, Yongguang, Zhao, Feng, Liu, Jin, Xiao, Shunping |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2017
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5375918/ https://www.ncbi.nlm.nih.gov/pubmed/28335492 http://dx.doi.org/10.3390/s17030632 |
Ejemplares similares
-
An End-to-End Deep Learning Approach for State Recognition of Multifunction Radars
por: Xu, Xinsong, et al.
Publicado: (2022) -
Two-Dimensional Augmented State–Space Approach with Applications to Sparse Representation of Radar Signatures
por: Wu, Kejiang, et al.
Publicado: (2019) -
A Radar Signal Recognition Approach via IIF-Net Deep Learning Models
por: Li, Ji, et al.
Publicado: (2020) -
Clustered Multi-Task Learning for Automatic Radar Target Recognition
por: Li, Cong, et al.
Publicado: (2017) -
A Multipulse Radar Signal Recognition Approach via HRF-Net Deep Learning Models
por: Li, Ji, et al.
Publicado: (2021)