TDOA Positioning with BDS+5G Space-Time Datum

Abstract

Objectives: With the establishment of the positioning enhancement project in the 3rd generation partnership project to meet further positioning requirements, the positioning performance of the 5th genera‑ tion mobile communication technology(5G) has been greatly improved. Currently, researches on 5G com‑ munication positioning are mainly conducted through channel simulators. Methods: We validated the Chan algorithm, the Taylor series expansion algorithm, and the residual weighting (RWGH) algorithm using real 5G n78 positioning reference signal (PRS) at 3 400－3 600 MHz from eight pico base stations. Centimeter-level space datum and nanosecond-level time synchronization were built relying on BeiDou satellite naviga‑ tion system in two typical indoor test scenarios. One 5G receiver was set at several reference points with two antennas to collect static positioning data. For kinematic positioning, we used a handcart with 5G re‑ ceiver on it to walk along with the reference square traces. Results: (1) The error rates of 5G PRS signal de‑ modulation were lower than 30%, and the integrity rates were over 80% at 1 Hz sample frequency. (2) The accuracy of time of differential arrival(TDOA) was below 0.5 m on average. But during some periods, the TDOA errors caused by non-line-of-sight (NLOS) could be 5 m or even more. (3) In static positioning tests, the accuracy of Chan algorithm was better than 1 m with line-of-sight condition, but the positioning accuracy of Chan algorithm decreased significantly when NLOS occurs. The Taylor algorithm also failed to provide accurate positioning results in those epochs. (4) In kinematic positioning tests, Taylor algorithm achieved 0.77 m accuracy, while the accuracy of RWGH algorithm was 0.91 m. The error of Chan algo‑ rithm was larger than 1 m. Conclusions: We have a better understanding about those maximum likelihood estimations and their applications and limitations. The RWGH algorithm shows improvement both in static and kinematic positioning tests, while the Chan algorithm is not suitable for complex indoor scenario with certain multipath effect. Still, the multipath effect and the NLOS error are the key factors to be solved in in‑ door positioning. Further research on 5G indoor and outdoor location combination with satellite observation and inertial navigation system is also needed.