CNN-LSTM Radar Signal Sorting Algorithm Fusing Intra-pulse and Inter-pulse Multi-dimensional Features
Year: 2025
Type: conference-paper
Abstract: Aiming at the low sorting accuracy of the traditional radar signal sorting algorithm under the aliasing of parameters and modulation forms of radar signal pulses, this paper propose a radar signal sorting algorithm based on the fusion of intra-pulse and inter-pulse multi-dimensional features. Firstly, multiple intra-pulse features of radar signals are extracted and combined with inter-pulse parameters to form a multi-dimensional feature matrix. Then, signals are pre-sorted through the DBSCAN clustering algorithm. Finally, the main sorting of radar signals is realized based on the proposed CNN-LSTM neural network. Simulation results demonstrate that compared with support vector machine (SVM), CNN, and LSTM networks, the proposed CNN-LSTM algorithm has great advantages in the sorting accuracy of radar signals, reaching 98.3%.
Authors: Tianyu Gao, Chunjie Zhang, Xiaohan Zhang
Institution: Harbin Engineering University
Language: English
Subfield: Aerospace Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W4410812946