A novel radar signal recognition method based on a deep restricted Boltzmann machine
Keywords:
radar signal recognition, deep learning, restricted Boltzman machine, RSRDRBMAbstract
Radar signal recognition is of great importance in the field of electronic intelligence reconnaissance. To deal with the problem of parameter complexity and agility of multi-function radars in radar signal recognition, a new model called radar signal recognition based on the deep restricted Boltzmann machine (RSRDRBM) is proposed to extract the feature parameters and recognize the radar emitter. This model is composed of multiple restricted Boltzmann machines. A bottom-up hierarchical unsupervised learning is used to obtain the initial parameters, and then the traditional back propagation (BP) algorithm is conducted to fine-tune the network parameters. Softmax algorithm is used to classify the results at last. Simulation and comparison experiments show that the proposed method has the ability of extracting the parameter features and recognizing the radar emitters, and it is characterized with strong robustness as well as highly correct recognition rate.Downloads
Published
Issue
Section
License
Engineering review uses the Creative Commons Attribution-NonCommercial-NoDerivatives (CC-BY-NC-ND) 4.0 International License, which governs the use, publishing and distribution of articles by authors, publishers and the wider general public.
The authors are allowed to post a digital file of the published article, or the link to the published article (Enginering Review web page) may be made publicly available on websites or repositories, such as the Author’s personal website, preprint servers, university networks or primary employer’s institutional websites, third party institutional or subject-based repositories, and conference websites that feature presentations by the Author(s) based on the published article, under the condition that the article is posted in its unaltered Engineering Review form, exclusively for non-commercial purposes.
The journal Engineering Review’s publishing procedure is performed in accordance with the publishing ethics statements, defined within the Publishing Ethics Resource Kit. The Ethics statement is available in the document Ethics Policies.