Pedestrian Dead Reckoning (PDR) is a good alternative positioning method in Global Navigation Satellite Systems (GNSS)-challenged environments. It has the advantage in terms of infrastructure-independent, while the disadvantage is that, the estimated errors grow rapidly with time. The Digital Terrestrial Multimedia Broadcasting (DTMB) signals have strong transmission power, which contributes to better urban propagation and building penetration than GNSS signals. So, in this paper, an enhanced PDR algorithm aided with DTMB signals is proposed. In the study, a complete software-defined radio receiver is developed to estimate the Doppler speed and range information from DTMB signals. To reduce the accumulated errors of the PDR, the Extended Kalman Filter (EKF) algorithm is carried out to fuse the information of Doppler speed and ranging from the DTMB signals, as well as the information of walking speed and heading from the PDR. The results of the field tests showed that the 95% positioning error of the proposed algorithm is less than 3.94 m, while the PDR only is less than 9.19 m, which suggests the effectiveness of the proposed method to provide continuous positioning by fusing DTMB signals with PDR.

中文翻译：

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DTMB 信号辅助的增强行人航位推算

行人航位推算 (PDR) 是全球导航卫星系统 (GNSS) 挑战环境中一种很好的替代定位方法。它在独立于基础设施方面具有优势，而缺点是估计误差随时间迅速增长。数字地面多媒体广播 (DTMB) 信号具有强大的传输功率，与 GNSS 信号相比，它有助于更​​好地进行城市传播和建筑物穿透。因此，本文提出了一种辅助DTMB信号的增强型PDR算法。在这项研究中，开发了一个完整的软件定义无线电接收器来估计来自 DTMB 信号的多普勒速度和距离信息。为了减少 PDR 的累积误差，采用扩展卡尔曼滤波（EKF）算法融合DTMB信号的多普勒速度和测距信息，以及PDR的步行速度和航向信息。现场测试结果表明，该算法的95%定位误差小于3.94 m，而PDR仅小于9.19 m，这表明该算法通过融合DTMB信号和连续定位提供连续定位的有效性。人民民主共和国。