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Radars are widely adopted for autonomous navigation and vehicular networking due to their robustness to weather conditions as compared to visible light cameras and lidars. However, radars currently struggle with differentiating static vs tangentially moving objects within a single radar frame since both yield the same Doppler along line-of-sight paths to the radar. Prior solutions deploy multiple radar or visible light camera modules to form a multi-“look” synthetic aperture for estimating the single-frame velocity vectors, to estimate tangential and radial velocity components of moving objects leading to higher system costs. In this paper, we propose to exploit multi-bounce scattering from secondary static objects in the environment, e.g., building pillars, walls, etc., to form an effective multi-“look” synthetic aperture for single-frame velocity vector estimation with a single multiple-input, multiple-output (MIMO) radar, thus reducing the overall system cost and removing the need for multi-module synchronization. We present a comprehensive theoretical and experiment evaluation of our scheme, demonstrating a 4.5× reduction in the error for estimating moving objects’ velocity vectors over comparable single-radar baselines.
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This content will become publicly available on March 7, 2026
Through-the-Wall Multi-Person Localization using Translation and Rotation Synthetic Aperture Radar
An emerging application of wireless sensing is locating and tracking humans in their living environments, a primitive that can be leveraged in both daily life applications and emergency situations. However, most proposed methods have limited spatial resolution when multiple humans are in close vicinity. The problem becomes exacerbated when there is no line-of-sight path to the humans. In this paper, we consider multi-person localization of humans in close vicinity of each other. We propose the use of synthetic aperture radar that combines both translation and rotation to increase effective aperture size, leveraging small rhythmic changes in the radar range due to human breathing. We experimentally evaluate the proposed algorithm in both line-of-sight and through-wall cases with three to five humans in the scene. Our experimental results show that: (i) larger synthetic apertures due to radar translation improve multi-person localization, e.g., by 1.42× when the aperture size is increased by a factor of 2×, and (ii) rotation can largely compensate for gains provided by translation, e.g., rotating the radar over 360° without changing the aperture size results in 1.22× gains over no rotation. Overall, maximal gains of 2.19× are achieved by rotating and translating over a 2× larger aperture.
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- Award ID(s):
- 2215082
- PAR ID:
- 10652528
- Publisher / Repository:
- IEEE Xplore
- Date Published:
- Journal Name:
- Proceedings of the IEEE International Conference on Acoustics Speech and Signal Processing
- ISSN:
- 2379-190X
- Page Range / eLocation ID:
- 1 to 5
- Subject(s) / Keyword(s):
- Multi-Person Localization Synthetic Aperture Radar UWB Radar Translation and Rotation Radar
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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