Cooperative Bistatic ISAC Systems for Low-Altitude Economy

TL;DR

This paper introduces a cooperative bistatic ISAC system within 5G infrastructure for low-altitude economy applications, achieving high-accuracy multi-target localization and velocity estimation with efficient algorithms and robust data fusion.

Contribution

It proposes a novel cooperative bistatic ISAC framework with a low-complexity tensor-based parameter extraction and a robust MST-based data fusion scheme for improved sensing performance.

Findings

Enhanced localization accuracy in low-altitude scenarios

Reduced computational complexity of parameter estimation

Effective data association and fusion for joint position and velocity recovery

Abstract

The burgeoning low-altitude economy (LAE) necessitates integrated sensing and communication (ISAC) systems capable of high-accuracy multi-target localization and velocity estimation under hardware and coverage constraints inherent in conventional ISAC architectures. This paper addresses these challenges by proposing a cooperative bistatic ISAC framework within MIMO-OFDM cellular networks, enabling robust sensing services for LAE applications through standardized 5G New Radio (NR) infrastructure. We first develop a low-complexity parameter extraction algorithm employing CANDECOMP/PARAFAC (CP) tensor decomposition, which exploits the inherent Vandermonde structure in delay-related factor matrices to efficiently recover bistatic ranges, Doppler velocities, and angles-of-arrival (AoA) from multi-dimensional received signal tensors. To resolve data association ambiguity across distributed transmitter-receiver pairs and mitigate erroneous estimates, we further design a robust fusion scheme based on the minimum spanning tree (MST) method, enabling joint 3D position and velocity reconstruction. Comprehensive simulation results validate the framework's superiority in computational efficiency and sensing performance for low-altitude scenarios.