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Related Experiment Video

Updated: May 12, 2026

Time Multiplexing Super Resolving Technique for Imaging from a Moving Platform

Time Multiplexing Super Resolving Technique for Imaging from a Moving Platform

Published on: February 12, 2014

Localization and mapping using only a rotating FMCW radar sensor.

Damien Vivet¹, Paul Checchin, Roland Chapuis

¹Institut Pascal, Université Blaise Pascal, Clermont Université, Clermont-Ferrand, France. damien.vivet@univ-bpclermont.fr

Sensors (Basel, Switzerland)

|April 10, 2013

Summary

This summary is machine-generated.

This study uses distortions in radar data, not noise correction, to track vehicle movement. This novel approach enables radar-only localization and mapping for high-speed ground robots without external sensors.

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Last Updated: May 12, 2026

Time Multiplexing Super Resolving Technique for Imaging from a Moving Platform

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Published on: February 12, 2014

Tracking Infiltration Front Depth Using Time-lapse Multi-offset Gathers Collected with Array Antenna Ground Penetrating Radar

Tracking Infiltration Front Depth Using Time-lapse Multi-offset Gathers Collected with Array Antenna Ground Penetrating Radar

Published on: May 1, 2018

Area of Science:

Robotics
Sensor Fusion
Computer Vision

Background:

Rotating radar sensors are underutilized in mobile robotics.
Panoramic radar provides distance and velocity for multiple targets.
High-speed robotics introduces geometric and Doppler velocity distortions in radar data.

Purpose of the Study:

To investigate the use of geometric and Doppler distortions as information sources.
To estimate vehicle displacement using radar data distortions.
To achieve radar-only localization and mapping for high-speed ground vehicles.

Main Methods:

Analyzing distortions in Frequency Modulated Continuous Wave (FMCW) radar measurements from the IMPALA sensor.
Estimating linear and angular velocities of the mobile robot based on distortion analysis.
Utilizing velocity estimates for trajectory construction and radar mapping.

Main Results:

Successful estimation of vehicle displacement without proprioceptive sensors.
Demonstration of radar-only localization and mapping capabilities.
Presentation of results for a ground vehicle operating at high speeds.

Conclusions:

Radar data distortions and Doppler effects can be leveraged for accurate vehicle localization and mapping.
This method offers a sensor-fusion-free alternative for mobile robot navigation.
The approach is effective for high-speed ground vehicle applications.