Sensing With Unknown Signals: ISAC Enabled Distributed Passive Sensing for Multi-Target Detection and Localization

Integrated sensing and communication (ISAC) has been recognized as a critical usage scenario for the 6th generation (6G) networks, covering a vast variety of use cases. As wireless systems are densely deployed, signals transmitted by network nodes are pervasive in the environment, making it possible to opportunistically receive these signals and exploit them for passive sensing. This motivates distributed passive sensing systems that consist only of receivers and rely on signals emitted by noncooperative transmitters. In this paper, a distributed passive sensing system that operates with completely unknown signals is proposed and studied. As a first step, a blind channel identification based method is proposed for target detection, where the presence of targets is inferred from peaks in the estimated equivalent channel response. Then, the system functionality is extended to support multitarget localization. The resulting measurements across distributed receivers lead to a data association problem, for which we formulate a suitable model and propose a coping strategy to correctly associate observations. Numerical results demonstrate the feasibility and accuracy of the proposed method enabling target detection and localization using unknown signals and singleantenna, lowcost receivers.