Abstract
Estimating channel parameters such as azimuth, elevation, Doppler shift, and delay is a key challenge in wireless communication, often formulated as a multidimensional harmonic retrieval (MHR) problem. To address this, we propose a high-order dynamic mode decomposition (HODMD) framework for robust frequency estimation from high-dimensional signals in noisy environments. The HODMD approach combines high-order singular value decomposition (HOSVD) to decompose tensor data into a core tensor and mode matrices, with dynamic mode decomposition (DMD) to extract frequencies from the imaginary parts of the DMD eigenvalues. Simulation examples validate the effectiveness of the proposed method, demonstrating its efficiency in solving MHR problems.
Recommended Citation
Y. Zhang et al., "High-Order Dynamic Mode Decomposition for Multidimensional Harmonic Retrieval," 2025 Asia Pacific International Symposium and Exhibition on Electromagnetic Compatibility Apemc 2025, pp. 376 - 378, Institute of Electrical and Electronics Engineers, Jan 2025.
The definitive version is available at https://doi.org/10.1109/APEMC62958.2025.11051397
Department(s)
Mechanical and Aerospace Engineering
Keywords and Phrases
dynamic mode decomposition; high-order dynamic mode decomposition; high-order singular value decomposition; Multidimensional harmonic retrieval
Document Type
Article - Conference proceedings
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2025 Institute of Electrical and Electronics Engineers, All rights reserved.
Publication Date
01 Jan 2025
Comments
Innovation and Technology Fund, Grant 14201923