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Low-Complexity 5g Slam with CKF-PHD Filter
- Authors
- Kim, Hyowon; Granstrom, Karl; Kim, Sunwoo; Wymeersch, Henk
- Issue Date
- May-2020
- Publisher
- Institute of Electrical and Electronics Engineers Inc.
- Keywords
- 5G mmWave; CKF; cooperative SLAM; message passing; multi-model PHD
- Citation
- ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings, v.2020, no.May, pp.5220 - 5224
- Indexed
- SCOPUS
- Journal Title
- ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
- Volume
- 2020
- Number
- May
- Start Page
- 5220
- End Page
- 5224
- ISSN
- 0736-7791
- Abstract
- In 5G mmWave, simultaneous localization and mapping (SLAM) allows devices to exploit map information to improve their position estimate. Even the most basic SLAM filter based on a Rao-Blackwellized particle filter (RBPF) combined with a probability hypothesis density (PHD) map representation exhibits high complexity. This paper proposes a new implementation method for the 5G SLAM using message passing (MP) and the cubature Kalman filter (CKF). We demonstrate that the proposed method significantly reduces the complexity while retaining the SLAM accuracy of the RBPF-PHD approach.
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Related Researcher
- Kim, Sunwoo
- COLLEGE OF ENGINEERING (SCHOOL OF ELECTRONIC ENGINEERING)