Due to the emergence of various wireless sensing technologies, numerous positioning algorithms have been introduced in the literature, categorized into \emph{geometry-driven positioning} (GP) and \emph{data-driven positioning} (DP). These approaches have respective limitations, e.g., a non-line-of-sight issue for GP and the lack of a labeled dataset for DP, which can be complemented by integrating both methods. To this end, this paper aims to introduce a novel principle called \emph{combinatorial data augmentation} (CDA), a catalyst for the two approaches' seamless integration. Specifically, GP-based datasets augmented from different combinations of positioning entities, called \emph{preliminary estimate locations} (PELs), can be used as DP's inputs. We confirm the CDA's effectiveness from field experiments based on WiFi \emph{round-trip times} (RTTs) and \emph{inertial measurement units} (IMUs) by designing several CDA-based positioning algorithms. First, we show that CDA offers various metrics quantifying each PEL's reliability, thereby filtering out unreliable PELs for WiFi RTT positioning. Second, CDA helps compute the measurement covariance matrix of a Kalman filter for fusing two position estimates derived by WiFi RTT and IMUs. Third, we use the above position estimate as the corresponding PEL's real-time label for fingerprint-based positioning as a representative DP algorithm. It provides accurate and reliable positioning results, says an average positioning error of $1.51$ (m) with a standard deviation of $0.88$~(m).

翻译：随着多种无线传感技术的涌现，文献中提出了大量定位算法，可分为\emph{几何驱动定位}（GP）和\emph{数据驱动定位}（DP）。这两类方法各有局限性，例如GP面临非视距问题，而DP则缺乏带标签数据集，通过融合两种方法可互补不足。为此，本文旨在提出一项名为\emph{组合数据增强}（CDA）的新原理，作为两种方法无缝融合的催化剂。具体而言，通过不同定位实体组合增强得到的基于GP的数据集——称为\emph{初步估计位置}（PELs），可作为DP的输入。我们基于WiFi \emph{往返时间}（RTT）和\emph{惯性测量单元}（IMU）设计多种基于CDA的定位算法，并通过现场实验验证其有效性。首先，我们证明CDA能提供量化每个PEL可靠性的多种度量，从而过滤不可靠的PEL用于WiFi RTT定位。其次，CDA有助于计算卡尔曼滤波器的测量协方差矩阵，以融合由WiFi RTT和IMU得到的两个位置估计值。第三，我们将上述位置估计值作为对应PEL的实时标签，用于指纹定位（一种代表性DP算法）。该方法能提供准确且可靠的定位结果，平均定位误差为$1.51$米，标准差为$0.88$米。