Optimally Deployed Multistatic OTFS-ISAC Design With Kalman-Based Tracking of Targets

2026-02-10

AI Summary

This work proposes a multisite integrated sensing and communication (ISAC) architecture to address the co-design challenge of high-precision localization and robust high-speed communication in vehicular networks. By integrating orthogonal time-frequency-space (OTFS) modulation, trilateration, and Kalman filtering, the study devises a suboptimal receiver placement strategy that effectively optimizes the spatial configuration of sensing nodes. The proposed approach significantly enhances target localization and velocity estimation accuracy in dynamic scenarios while simultaneously reducing communication bit error rates. Numerical experiments demonstrate that the scheme achieves superior sensing performance and reliable communication in complex vehicular environments, validating its effectiveness and practicality.

Technology Category

• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Intelligent Robots: Localization, Mapping, and Navigation
• Search and Optimization: Mixed Discrete/Continuous Search

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Location- and context-aware Web and WoT applications and services
• Security and Privacy: Large-scale security measurements
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs

Abstract

This paper studies orthogonal time-frequency space (OTFS) modulation aided multistatic integrated sensing and communication (ISAC) in vehicular networks, whereby its delay-Doppler robustness is exploited for enhanced communication and high-resolution sensing. We present a triangulation-based deployment framework combined with Kalman filtering (KF) that enables accurate target localization and velocity estimation. In addition, we assess the ISAC performance in the multistatic topology to determine its effectiveness in the dynamic environment. Further, a suboptimal placement strategy for the multistatic receivers is devised to reduce the targets'localization error. Numerical results demonstrate significant reductions in the sensing error and bit error rate (BER) performances.

Problem

• OTFS
• ISAC
• multistatic
• target localization
• vehicular networks

Innovation

• OTFS
• multistatic ISAC
• Kalman filtering
• triangulation-based deployment
• target localization