Vehicular Multistatic OTFS-ISAC: A Geometry-Aware Deployment and Kalman-Based Tracking
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arXiv
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| Format: | Preprint |
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2025
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| _version_ | 1866915787741069312 |
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| author | Rani, Jyotsna Deka, Kuntal Prasad, Ganesh Liu, Zilong |
| author_facet | Rani, Jyotsna Deka, Kuntal Prasad, Ganesh Liu, Zilong |
| contents | Integrated sensing and communication (ISAC) is a promising paradigm for next-generation vehicular networks, yet existing orthogonal frequency-division multiplexing (OFDM)-based designs suffer from limited spatial diversity and severe sensitivity to Doppler and multipath effects. While orthogonal time-frequency space (OTFS) modulation offers robustness under high mobility, the impact of spatial node deployment in multistatic OTFS-ISAC has remained largely unexplored. This paper presents the first geometry-aware multistatic OTFS-ISAC framework, in which a triangulation-based cooperative sensing approach is developed for joint target localization and velocity estimation. Closed-form expressions for the localization error covariance are derived under general receiver topologies, revealing that maximizing the triangulation area is fundamental to minimizing estimation error. This leads to a near-optimal deployment strategy based on orthogonal receiver placement and its equivalence to multi-antenna architectures with cubic-order error reduction. To enable reliable tracking of moving targets, a correlated random walk (CRW)-based Kalman filter (KF) framework is integrated into multistatic OTFS-ISAC for active sensing and ISAC. Numerical results demonstrate significant reductions in localization root-mean-square error (RMSE) and communication bit error rate (BER), highlighting the effectiveness of geometry-aware, KF-assisted multistatic OTFS-ISAC in dynamic vehicular environments. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2509_16700 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Vehicular Multistatic OTFS-ISAC: A Geometry-Aware Deployment and Kalman-Based Tracking Rani, Jyotsna Deka, Kuntal Prasad, Ganesh Liu, Zilong Networking and Internet Architecture Integrated sensing and communication (ISAC) is a promising paradigm for next-generation vehicular networks, yet existing orthogonal frequency-division multiplexing (OFDM)-based designs suffer from limited spatial diversity and severe sensitivity to Doppler and multipath effects. While orthogonal time-frequency space (OTFS) modulation offers robustness under high mobility, the impact of spatial node deployment in multistatic OTFS-ISAC has remained largely unexplored. This paper presents the first geometry-aware multistatic OTFS-ISAC framework, in which a triangulation-based cooperative sensing approach is developed for joint target localization and velocity estimation. Closed-form expressions for the localization error covariance are derived under general receiver topologies, revealing that maximizing the triangulation area is fundamental to minimizing estimation error. This leads to a near-optimal deployment strategy based on orthogonal receiver placement and its equivalence to multi-antenna architectures with cubic-order error reduction. To enable reliable tracking of moving targets, a correlated random walk (CRW)-based Kalman filter (KF) framework is integrated into multistatic OTFS-ISAC for active sensing and ISAC. Numerical results demonstrate significant reductions in localization root-mean-square error (RMSE) and communication bit error rate (BER), highlighting the effectiveness of geometry-aware, KF-assisted multistatic OTFS-ISAC in dynamic vehicular environments. |
| title | Vehicular Multistatic OTFS-ISAC: A Geometry-Aware Deployment and Kalman-Based Tracking |
| topic | Networking and Internet Architecture |
| url | https://arxiv.org/abs/2509.16700 |