Near-field integrated sensing and communication (ISAC) requires target models beyond the point-target abstraction when the target has a non-negligible spatial extent. In this letter, a geometry-aware transmit design is developed for a parametric extended target (ET) described by its center, orientation, and size under spherical-wave propagation. The CRB for the geometric parameters is formulated around a nominal ET state, an exact ET-aware reduced subspace is identified for the lifted covariance formulation, and a reduced-dimensional semidefinite relaxation (SDR) is developed under signal-to-interference-plus-noise ratio (SINR) and power constraints. Simulation results show lower CRB values than point-target and geometry-agnostic baselines together with substantially reduced runtime for large arrays.
@article{arxiv.2604.18166,
title = {Cram\'{e}r-Rao Bound Optimization for Near-Field ISAC with Extended Targets},
author = {Zongyao Zhao and Zhaolin Wang and Lincong Han and Liang Xu and Jing Jin and Yuanwei Liu and Kaibin Huang},
journal= {arXiv preprint arXiv:2604.18166},
year = {2026}
}