Differential Time of Arrival Based Opportunistic Positioning for Asynchronous Cellular Signals: Model, Algorithms and Experiments

Abstract

Signal asynchronism significantly challenges opportunistic cellular signal positioning. Existing solutions typically rely on global navigation satellite system (GNSS)-assisted initialization or multiterminal collaboration, resulting in limited application scenarios and high implementation costs. To overcome this, a differential time-of-arrival (DTOA)-based asynchronous cellular signal positioning system is developed. By treating the user equipment at the previous time as a differential reference, a DTOA positioning model is presented to implement asynchronous cellular positioning completely independently. The Taylor-series method, which has Cramer–Rao lower bound accuracy, is considered to solve the DTOA equations. To ensure global convergence, the two-step weighted least squares (TSWLS) method and its bias reduction methods are extended to DTOA positioning to obtain an initial position guess. The linear equations at each step are reconstructed, and TSWLS ambiguity is eliminated. Simulations are conducted to analyze the DTOA positioning geometry and the performance of the proposed algorithms. The proposed system implements preliminary positioning based on DTOA and exploits an extended Kalman filter for real-time positioning. It is validated experimentally, the DTOA and EKF positioning root mean-squared errors in the field test are 4.0 m and 4.2 m, respectively, which are close to the accuracy of a conventional system with GNSS-assisted initialization.