  Mobile communication networks were designed to mainly support ubiquitous
wireless communications, yet they are expected to also achieve radio sensing
capabilities in the near future. Most prior studies on radar sensing focus on
distant targets, which usually rely on far-field assumption with uniform plane
wave (UPW) models. However, with ever-increasing antenna size, together with
the growing need to also sense nearby targets, the far-field assumption may
become invalid. This paper studies radar sensing with extremely large-scale
(XL) antenna arrays, where a generic model that takes into account both
spherical wavefront and amplitude variations across array elements is
developed. Furthermore, new closed-form expressions of the sensing
signal-to-noise ratios (SNRs) are derived for both XL-MIMO radar and
XL-phased-array radar modes. Our results reveal that different from the
conventional UPW model where the SNR scales linearly and unboundedly with N for
MIMO radar and with MN for phased-array radar, with M and N being the transmit
and receive antenna numbers, respectively, more practical SNR scaling laws are
obtained. For XL-phased-array radar with optimal power allocation, the SNR
increases with M and N with diminishing returns, governed by new parameters
called the transmit and receive angular spans. On the other hand, for XL-MIMO
radar, while the same SNR scaling as XL-phased-array radar is obeyed for N, the
SNR first increases and then decreases with M.
