To address the challenges of high precision relying on dense beacon deployment and poor dynamic adaptability in Bluetooth indoor 3D localization, this paper aims to propose a hybrid sensor fusion measurement method that integrates connected-state phase ranging measurements with broadcast-state received signal strength indicator sensing from a single beacon, aiming to reduce deployment complexity while enhancing measurement robustness and sensor-based localization reliability.
A heterogeneous sensor fusion measurement framework is constructed to simultaneously acquire phase-based ranging (PBR) measurements from the connected state and received signal strength indicator (RSSI) sensing observations from the broadcast state under single-beacon conditions. By introducing a geometric constraint model that transforms sparse RSSI sensing data into spatial soft constraints, a lightweight nonlinear optimization problem is formulated. A hybrid optimization strategy combining golden spiral sampling with local perturbation search is used for efficient sensor measurement solution and an abnormal drift trigger mechanism is introduced to enhance measurement robustness and sensor fusion convergence efficiency in dynamic environments.
Experimental sensor measurement results demonstrate that the proposed fusion measurement method reduces the mean localization error by 42.1% compared to conventional approaches. Accurate static and dynamic 3D positioning measurements are achieved using only one pair of connected Bluetooth low energy (BLE) devices as anchors, validating the effectiveness of the proposed sensor fusion measurement framework. The proposed abnormal drift trigger mechanism effectively suppresses unrealistic jumps, reducing the maximum measurement error by 14.6%. In dynamic trajectory tests, the root mean square error (RMSE) of the proposed sensor-based measurement method reaches 1.714 meters, with computational efficiency meeting real-time requirements for continuous sensing and positioning.
To the best of the authors’ knowledge, this study proposes, for the first time, a hybrid fusion measurement approach that integrates connected-state phase ranging with broadcast-state received signal strength indicator (RSSI) sensing from a single beacon. By synergistically combining high-precision phase measurement with adaptive RSSI perception, the proposed method achieves accurate 3D positioning comparable to traditional multi-beacon architectures using only a single connected pair. This work provides a new pathway for low-cost, easily deployable indoor positioning systems, highlighting the role of intelligent fusion measurement in signal-constrained environments.
