On Hybrid Radar Fusion for Integrated Sensing and Communication

TL;DR

This paper proposes a novel hybrid radar fusion approach in integrated sensing and communication systems, combining mono-static and bi-static radar techniques to improve target and user angle estimation.

Contribution

It introduces a new hybrid radar fusion scenario, derives a maximum likelihood criterion, and develops two efficient algorithms for angle estimation in ISAC systems.

Findings

Algorithms outperform existing methods in simulations

Significant improvements in angle estimation accuracy

Demonstrated robustness across various scenarios

Abstract

The following paper introduces a novel integrated sensing and communication (ISAC) scenario termed hybrid radar fusion. In this setting, the dual-functional radar and communications (DFRC) base station (BS) acts as a mono-static radar in the downlink (DL), for sensing purposes, while performing its DL communication tasks. Meanwhile, the communication users act as distributed bi-static radar nodes in the uplink (UL) following a frequency-division duplex protocol. The DFRC BS fuses the information available at different DL and UL resource bands to estimate the angles-of-arrival (AoAs) of the multiple targets existing in the scene. In this work, we derive the maximum likelihood (ML) criterion for the hybrid radar fusion problem at hand. Additionally, we design efficient estimators; the first algorithm is based on an alternating optimization approach to solve the ML criterion, while the second one designs an optimization framework that leads to an alternating subspace approach to estimate AoAs for both the target and users. Finally, we demonstrate the superior performance of both algorithms in different scenarios, and the gains offered by these proposed methods through numerical simulations.