MULTI-SCOUT: Multistatic Integrated Sensing and Communications in 5G and Beyond for Moving Target Detection, Positioning, and Tracking

TL;DR

This paper develops a comprehensive signal-processing framework for multistatic integrated sensing and communications using 5G PRS signals, enabling accurate detection, positioning, and tracking of moving targets in 2D and 3D environments.

Contribution

It introduces a novel multistatic ISAC approach with a complete processing chain, including target detection, parameter estimation, and tracking, extended to multiple targets and real-world conditions.

Findings

High-fidelity moving target detection achieved.

Accurate 2D and 3D positioning demonstrated.

Effective tracking with Kalman filters.

Abstract

This paper presents a complete signal-processing chain for multistatic integrated sensing and communications (ISAC) using 5G Positioning Reference Signal (PRS). We consider a distributed architecture in which one gNB transmits a periodic OFDM-PRS waveform while multiple spatially separated receivers exploit the same signal for target detection, parameter estimation and tracking. A coherent cross-ambiguity function (CAF) is evaluated to form a range-Doppler map from which the bistatic delay and radial velocity are extracted for every target. For a single target, bistatic delays are fused through nonlinear least-squares trilateration, yielding a geometric position estimate, and a regularized linear inversion of the radial-speed equations yields a two-dimensional velocity vector, where speed and heading are obtained. The approach is applied to 2D and 3D settings, extended to account for receiver clock synchronization bias, and generalized to multiple targets by resolving target association. The sequence of position-velocity estimates is then fed to standard and extended Kalman filters to obtain smoothed tracks. Our results show high-fidelity moving-target detection, positioning, and tracking using 5G PRS signals for multistatic ISAC.