In this paper, we introduce an innovative approach for extracting
trajectories from a camera sensor in GPS-denied environments, leveraging visual
odometry. The system takes video footage captured by a forward-facing camera
mounted on a vehicle as input, with the output being a chain code representing
the camera's trajectory. The proposed methodology involves several key steps.
Firstly, we employ phase correlation between consecutive frames of the video to
extract essential information. Subsequently, we introduce a novel chain code
method termed "dynamic chain code," which is based on the x-shift values
derived from the phase correlation. The third step involves determining
directional changes (forward, left, right) by establishing thresholds and
extracting the corresponding chain code. This extracted code is then stored in
a buffer for further processing. Notably, our system outperforms traditional
methods reliant on spatial features, exhibiting greater speed and robustness in
noisy environments. Importantly, our approach operates without external camera
calibration information. Moreover, by incorporating visual odometry, our system
enhances its accuracy in estimating camera motion, providing a more
comprehensive understanding of trajectory dynamics. Finally, the system
culminates in the visualization of the normalized camera motion trajectory.

通过视觉里程计从 GPS 受限环境中的相机传感器中提取轨迹的创新方法，系统利用车辆上安装的前置摄像头捕捉的视频素材作为输入，输出为表示摄像头轨迹的链码。该方法基于相位相关对视频连续帧进行信息提取，并引入基于相位相关的 x 轴偏移值的新型链码方法即 “动态链码”，通过建立阈值来确定方向变化（前进、左转、右转），并提取相应的链码。该系统不依赖于空间特征的传统方法，在嘈杂环境中表现出更高的速度和稳健性，而且不需要外部摄像头校准信息。通过融合视觉里程计，该系统提高了对相机运动的精确估计的准确性，提供了对轨迹动态的更全面的理解。最后，系统将归一化摄像头运动轨迹可视化。

基于相位相关的前置摄像头视频轨迹近似

Trajectory Approximation of Video Based on Phase Correlation for Forward  Facing Camera

A robust and accurate positioning solution is required to increase the safety
in GPS-denied environments. Although there is a lot of available research in
this area, little has been done for confined environments such as tunnels.
Therefore, we organized a measurement campaign in a basement tunnel of
Link\"{o}ping university, in which we obtained ultra-wideband (UWB) complex
impulse responses for line-of-sight (LOS), and three non-LOS (NLOS) scenarios.
This paper is focused on time-of-arrival (TOA) ranging since this technique can
provide the most accurate range estimates, which are required for range-based
positioning. We describe the measurement setup and procedure, select the
threshold for TOA estimation, analyze the channel propagation parameters
obtained from the power delay profile (PDP), and provide statistical model for
ranging. According to our results, the rise-time should be used for NLOS
identification, and the maximum excess delay should be used for NLOS error
mitigation. However, the NLOS condition cannot be perfectly determined, so the
distance likelihood has to be represented in a Gaussian mixture form. We also
compared these results with measurements from a mine tunnel, and found a
similar behavior.

本文以 Linkoping 大学的地下隧道对频谱的复数脉冲响应进行了测量研究，重点阐述了 TOA 测距技术在建立基于距离的定位系统中的应用，并提供了 NLOS 识别误差和传播参数分析结果。