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

Jyotsna Rani, Kuntal Deka, Ganesh Prasad, Zilong Liu

TL;DR

This work addresses robust sensing and communication in highly dynamic vehicular networks by marrying OTFS waveform advantages with multistatic geometry. It develops a triangulation- and KF-based framework to localize and track targets while optimizing receiver topology to maximize triangulation area. The approach delivers significant reductions in localization error and BER, with KF-assisted and optimally deployed ISAC achieving the best performance. The findings highlight the practical benefits of geometry-aware deployment and Kalman filtering for reliable, high-resolution sensing and communication in next-generation connected-vehicle networks.

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.

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

TL;DR

This work addresses robust sensing and communication in highly dynamic vehicular networks by marrying OTFS waveform advantages with multistatic geometry. It develops a triangulation- and KF-based framework to localize and track targets while optimizing receiver topology to maximize triangulation area. The approach delivers significant reductions in localization error and BER, with KF-assisted and optimally deployed ISAC achieving the best performance. The findings highlight the practical benefits of geometry-aware deployment and Kalman filtering for reliable, high-resolution sensing and communication in next-generation connected-vehicle networks.

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.
Paper Structure (5 sections, 2 theorems, 27 equations, 4 figures, 2 algorithms)

This paper contains 5 sections, 2 theorems, 27 equations, 4 figures, 2 algorithms.

Table of Contents

  1. Introduction
  2. System Architecture
  3. Targets Localization Via Cooperative Sensing
  4. Multistatic Sensing and ISAC
  5. Numerical Results and Conclusion

Key Result

Lemma 1

For the given variances, $\{\sigma_{i,q}^2 \mid q \in \{0, j, k\}\}$ in the estimation of the square of the ranges of the $i$th target from the nodes, $\mathcal{A}_0$, $\mathcal{R}_j$, and $\mathcal{R}_k$, one can minimize $\operatorname{tr}(\operatorname{cov}(\widehat{\alpha}_{i},\widehat{\beta}_{i

Figures (4)

  • Figure 1: Network topology for multistatic ISAC.
  • Figure 2: Estimation of location and velocity of a target via cooperative sensing.
  • Figure 3: RMSE improvement with SNR for different numbers of targets.
  • Figure 4: Performance comparison of different schemes.

Theorems & Definitions (4)

  • Lemma 1
  • proof
  • Corollary 1
  • proof