Positioning and sensing over wireless networks are imperative for many emerging applications. However, since traditional wireless channel models over-simplify the user equipment (UE) as a point target, they cannot be used for sensing the attitude of the UE, which is typically described by the spatial orientation. 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 Cramér-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.

中文翻译：

---

基于电磁传播模型的近场定位和姿态感知


对于许多新兴应用来说，通过无线网络进行定位和传感是必不可少的。然而，由于传统的无线信道模型将用户设备（UE）过度简化为点目标，因此它们不能用于感测UE的姿态，而UE的姿态通常由空间定向来描述。本文开发了一种基于电磁理论的综合电磁传播建模（EPM）来精确模拟近场信道。对于无噪声情况，EPM 模型建立了观测信号对 UE 位置和姿态的非线性函数依赖性。为了解决非线性耦合的困难，我们首先提出将距离域划分为三个区域，由定义的相位模糊距离和间距约束距离分隔开。然后，对于每个区域，我们获得低复杂度的关节位置和姿态估计的闭式解。接下来，为了研究随机噪声对联合估计性能的影响，推导了 Ziv-Zakai 界限（ZZB）以产生有用的见解。进一步提供预期的 Cramér-Rao 界 (ECRB)，以获得性能下界的简化封闭式表达式。我们的数值结果表明，导出的 ZZB 可以在所有信噪比 (SNR) 范围内准确预测估计器的性能。更重要的是，我们的位置估计精度达到了毫米级，姿态估计精度达到了0.1级。