A computationally efficient 2D-root MUSIC parameter estimation for OCDM-based RadCom
| dc.contributor.author | Tiwana, Amna Javed | en |
| dc.contributor.author | Townsend, Paul D. | en |
| dc.contributor.author | Claussen, Holger | en |
| dc.contributor.author | Ouyang, Xing | en |
| dc.contributor.funder | Irish Research Council | en |
| dc.date.accessioned | 2026-02-23T15:57:37Z | |
| dc.date.available | 2026-02-23T15:57:37Z | |
| dc.date.issued | 2025 | en |
| dc.description.abstract | The next-generation of wireless communication is anticipated to integrate sensing and communication using a unified yet versatile waveform, capable of providing not only reliable data communication, but also localization and sensing functionality. Given the chirp-based structure of the recently proposed orthogonal chirp division multiplexing (OCDM), it has shown robustness against frequency selectiveness for communication but also suitability for sensing because of the inherent pulse compression property of the chirps. Although OCDM-based spectral resolution algorithms have been explored, polynomial root-based multiple signal classification (MUSIC) poses the issues of high-dimensionality and correct estimation assignment, especially for highly correlated multiple targets. In this paper, a computationally efficient two-dimensional high-resolution algorithm is proposed for joint range-velocity estimation for the OCDMbased Radar-Communication (RadCom) system. The proposed frequency domain radar processing for OCDM utilizes the eigendecomposition property of the Fresnel transform through a reduced polynomial-based root MUSIC algorithm, in conjunction with Gaussian pulses, to jointly localize synchronized targets. Polynomial dimensionality has been reduced by transforming the nonlinear polynomial into a linear eigenvalue problem. The eigen structure of the signal subspace is utilized to resolve the issue of estimation assignment for highly correlated multiple targets by minimizing the residual projection error. The numerical results for the proposed chirp-based pilot sensing demonstrate a significant improvement in sidelobes reduction over the typical 2D-FFT and 2D-MUSIC approach, for uncorrelated and highly correlated targets. Moreover, the algorithm avoids 2D exhaustive search as in conventional 2D-MUSIC, meanwhile, reducing the computational overhead of traditional OCDM radar processing. | en |
| dc.description.sponsorship | Irish Research Council (Grant no. GOIPD/2021/875) | en |
| dc.description.status | Peer reviewed | en |
| dc.description.version | Accepted Version | en |
| dc.format.mimetype | application/pdf | en |
| dc.identifier.citation | Tiwana, A. J., Townsend, P., Claussen, H. and Ouyang, X. (2025) 'A computationally efficient 2D-root MUSIC parameter estimation for OCDM-based RadCom', IEEE Global Communications Conference. Taipei, Taiwan, 8–12 December (6pp). | en |
| dc.identifier.endpage | 6 | en |
| dc.identifier.startpage | 1 | en |
| dc.identifier.uri | https://hdl.handle.net/10468/18559 | |
| dc.language.iso | en | en |
| dc.publisher | Institute of Electrical and Electronics Engineers (IEEE) | en |
| dc.rights | © 2025, IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. | en |
| dc.subject | OCDM RadCom | en |
| dc.subject | 2D root-MUSIC | en |
| dc.subject | Correlated signal | en |
| dc.title | A computationally efficient 2D-root MUSIC parameter estimation for OCDM-based RadCom | en |
| dc.type | Conference item | en |
