Positioning and sensing over wireless networks are imperative for many
emerging applications. However, traditional wireless channel models cannot be
used for sensing the attitude of the user equipment (UE), since they
over-simplify the UE as a point target. In this paper, a comprehensive
electromagnetic propagation modeling (EPM) based on electromagnetic theory is
developed to precisely model the near-field channel. For the noise-free case,
the EPM model establishes the non-linear functional dependence of observed
signals on both the position and attitude of the UE. To address the difficulty
in the non-linear coupling, we first propose to divide the distance domain into
three regions, separated by the defined Phase ambiguity distance and Spacing
constraint distance. Then, for each region, we obtain the closed-form solutions
for joint position and attitude estimation with low complexity. Next, to
investigate the impact of random noise on the joint estimation performance, the
Ziv-Zakai bound (ZZB) is derived to yield useful insights. The expected
Cram\'er-Rao bound (ECRB) is further provided to obtain the simplified
closed-form expressions for the performance lower bounds. Our numerical results
demonstrate that the derived ZZB can provide accurate predictions of the
performance of estimators in all signal-to-noise ratio (SNR) regimes. More
importantly, we achieve the millimeter-level accuracy in position estimation
and attain the 0.1-level accuracy in attitude estimation.Comment: 16 pages, 9 figures. Submitted to JSAC - Special Issue on Positioning
and Sensing Over Wireless Network