Low-power distance ranging for 2D-positioning using LoRa 2.4 GHz

• Demonstrates sub-2 m outdoor 2D localization using LoRa 2.4 GHz time-of-flight ranging in real-world outdoor scenario • Sixth-degree polynomial + LUT calibration reduces systematic bias across 0–150 m • Direct Linear Solve: 1.27 m DRMS; Least Squares: 0.94 m DRMS • Quantifies latency–accuracy trade-off: ≈ 200 ms at 20 exchanges, ≈ 600 ms at 100 • Measures ultra-low energy consumption ( ≈ 0.7 mJ/exchange), enabling multi-day operation • Provides empirical validation of integrated positioning for energy-constrained IoT networks Accurate, energy-efficient localization remains a key challenge for Internet of Things (IoT) applications such as sports tracking, warehouse automation, and robotics. While LoRa 2.4 GHz offers built-in time-of-flight (ToF) ranging, its practical performance in energy-constrained, real-world scenarios is not yet fully established. In this paper, we experimentally validate the feasibility of low-power 2D localization using Semtech SX1280 transceivers. We move beyond theoretical parameter studies to systematically quantify the trade-offs between ranging precision, latency, and energy consumption in an outdoor field deployment. Our evaluation comprises (i) a characterization of the accuracy-energy design space to identify optimal physical layer settings; (ii) a systematic bias calibration procedure using polynomial regression and lookup-table inversion; and (iii) field trials over a 6500 sqm sports field. The calibrated system yields reliable distance estimates up to 150 meters with sub-two-meter position accuracy. Using Direct Linear Solve (DLS) and nonlinear Least Squares (LSQ) trilateration, we achieve distance root mean square (DRMS) errors of 1.27 and 0.94 meters, respectively. Finally, we measure the energy cost to be approximately 0.7 mJ per ranging exchange, a value low enough to support multi-day operation at a 1 Hz update rate on standard batteries. These results provide a concrete, empirically validated baseline for integrating meter-level positioning into existing LoRa communication networks without additional hardware.