A Spatial Spectrum Estimation Algorithm for 3D Localization and Mapping in ISAC

In this paper, it considers the localization of passive targets and mapping for integrated sensing and communication (ISAC) in a Multi-antenna OFDM cellular network. A novel two-phase sensing framework based on a single base station (BS) or mobile station (MS) is proposed for passive targets like UAVs. In Phase I, we propose a three-dimensional multi-signal classification algorithm for passive targets’ location, to obtain the distance information of the target through estimating the time delay parameters for TOA estimation, and horizontal azimuth and elevation angles by fixed distance parameter for DOA estimation. In Phase II, the BS/MS receives location maps of passive targets from the MS/BS through communication and redraws the map by overlapping the coordinates on the axis for the corresponding passive targets. Consequently, the relative position between the BS and MS can be determined by analyzing the redrawn map, allowing for the assessment of accumulated location errors. Simulations are carried out to validate the proposed localization and mapping methods.