Joint Target-Tag Estimation in Ambient Backscatter-Based ISAC

Abstract

Integrated sensing and communication (ISAC) has emerged as a key paradigm for unifying radar sensing and wireless communications within a shared hardware and spectral framework. In parallel, ambient backscatter communication (AmBC) has gained attention as a low-power solution for enabling passive connectivity by modulating and reflecting existing radio-frequency signals. Motivated by these developments, this paper investigates an integrated sensing and ambient backscatter communication (ISABC) framework in which a dual-functional radar-communication (DFRC) transceiver jointly performs high-resolution target sensing and low-power tag detection in cluttered environments. Within this ISAC and AmBC setting, we develop a comprehensive system model that jointly captures the estimation of target and clutter parameters, including delay, Doppler shift, and complex reflectivity, together with the recovery of embedded AmBC tag symbols. The resulting DFRC signal model reveals strong coupling among direct-path reflections, clutter echoes, and passive backscatter signals, leading to a highly entangled estimation problem. To address this challenge, we propose a robust three-stage signal processing framework that sequentially estimates target and clutter parameters before detecting the AmBC tag message. This structured approach effectively disentangles the superimposed components, improving both sensing accuracy and communication reliability in ISAC systems. Extensive simulations, benchmarked against the Cramer-Rao lower bound (CRLB), demonstrate the superior estimation performance of the proposed DFRC-based solution. The results further highlight the fundamental trade-offs between sensing accuracy and backscatter communication efficiency in ISABC systems.