Vehicle Tracking for Urban Air Mobility Using 5G PRS

This project demonstrates the use of 5G New Radio (NR) Positioning Reference Signals (PRS) for tracking autonomous vehicles in Urban Air Mobility (UAM) scenarios. The example leverages MATLAB's 5G Toolbox to simulate a realistic urban environment and evaluate the performance of PRS-based positioning. The project highlights how ToA (Time of Arrival) measurements from multiple gNodeBs improve positioning accuracy and robustness under challenging urban conditions.

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Features

• Urban Mobility Simulation: Simulates an urban environment with realistic vehicle trajectories.
• Integration of 5G PRS: Demonstrates the generation, transmission, and reception of PRS signals.
• Positioning Accuracy: Evaluates performance using multi-gNodeB ToA measurements.
• Advanced Tracking: Implements tracking algorithms (e.g., Extended Kalman Filter) for trajectory refinement.
• Comprehensive Visualization: Includes 2D/3D trajectory plots and positioning error metrics.

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Repository Contents

• MATLAB Code:
  • generateUrbanScenario.m: Creates the urban environment and vehicle trajectory.
  • configurePRS.m: Configures the 5G PRS signals as per 3GPP standards.
  • simulateChannel.m: Simulates the urban multipath propagation channel.
  • processToA.m: Processes ToA measurements from received PRS signals.
  • applyTracking.m: Implements Kalman filtering for position tracking.
• Results:
  • trajectory.png: 3D visualization of the vehicle trajectory with uncertainty regions.
  • errorMetrics.png: Positioning error metrics and cumulative distribution.
• Documentation:
  • README.md: This file provides an overview of the project.
  • references.md: List of references and related 3GPP specifications.

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Requirements

• MATLAB R2023a or newer: The project requires MATLAB with the following toolboxes:
  • 5G Toolbox
  • Signal Processing Toolbox
  • Statistics and Machine Learning Toolbox
• System Requirements: Ensure your system meets MATLAB's minimum hardware requirements.

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How to Run

1. Clone or download the repository.
2. Open MATLAB and set the project directory as the current folder.
3. Run the main script:

   mainSimulation.m

4. View Results, Including Trajectory Plots and Error Metrics

Key Steps

Urban Scenario Generation:

• Define vehicle trajectory and gNodeB positions in a 3D urban layout.
• Simulate the environment using the generateUrbanScenario.m script.

PRS Configuration:

• Configure the PRS signals for transmission using 3GPP-compliant settings.
• Use configurePRS.m to set subcarrier spacing, periodicity, and bandwidth.

Channel Simulation:

• Simulate urban multipath propagation using a clustered delay line (CDL) model.
• Incorporate realistic impairments like NLoS (Non-Line-of-Sight) and Doppler shifts.

ToA Measurement:

• Process received PRS signals to estimate ToA.
• Use processToA.m to extract and refine ToA measurements.

Tracking:

• Fuse multi-gNodeB ToA data using Kalman filtering.
• Apply applyTracking.m to generate a smooth and accurate trajectory.

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Outputs

• Trajectory Visualization: 3D and 2D plots of vehicle path, estimated trajectory, and uncertainty regions.
• Error Metrics: Quantitative evaluation of positioning accuracy, including RMSE and cumulative error distributions.

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References

1. 3GPP TS 38.211: "NR; Physical channels and modulation"
2. 3GPP TS 38.855: "Study on NR positioning support"
3. MathWorks Documentation: Vehicle Tracking for Urban Air Mobility Using 5G PRS