Multi-Target Radar 3D Ego Motion Estimation Without ADMA
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Solution Overview
Problem
Automotive 3D radars often fail to provide accurate three-dimensional ranging and direction without calibration data, and advanced inertial measurement units like ADMA sensors are expensive and difficult to implement on all vehicles, necessitating an alternative and cost-effective method for continuous and precise 3D ego motion sensing.
Innovation Solution
A radar-based system that estimates 3D ego motion using signals from multiple sensors to detect stationary objects, calculating a vehicle's velocity and angular velocities through linear regression, allowing calibration without ADMA sensors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If ADMA sensors are used to provide precise 3D motion data for radar calibration, then measurement precision is improved, but device cost increases significantly
Solution Approach 1:
The patent creates a virtual copy of the ADMA sensor's calibration function by using the radar system itself to perform ego-motion estimation. Instead of relying on expensive physical ADMA sensors, the system processes radar signals from multiple stationary targets to compute velocity and orientation data, effectively copying the calibration capability at lower cost
Solution Approach 2:
The radar system performs self-calibration by using its own measurements of stationary targets to estimate its ego-motion. The system serves its own calibration needs without requiring external ADMA sensors, reducing dependency on expensive external devices while maintaining measurement precision
2Adaptability or versatility
If ADMA sensors are installed on all vehicles for radar calibration, then calibration data availability is improved, but device complexity increases
Solution Approach 1:
The patent makes the radar system multi-functional by enabling it to perform both its primary detection function and its own calibration function. The same radar hardware that detects objects is also used to estimate ego-motion and provide calibration data, eliminating the need for separate ADMA sensors on each vehicle
Solution Approach 2:
The system copies the calibration functionality from external ADMA sensors into the radar system itself, allowing any vehicle with a multi-antenna radar to perform calibration without requiring additional specialized sensors, thereby improving adaptability across different vehicle types
3Measurement precision
If traditional radar calibration methods using multiple stationary targets are used, then calibration accuracy is improved, but processing time increases due to object tracking requirements
Solution Approach 1:
The patent replaces the traditional mechanical/object tracking approach with a direct signal processing method. Instead of tracking objects over time to infer motion, the system uses Doppler velocity measurements from multiple stationary targets simultaneously to estimate ego-motion through linear regression, significantly reducing processing time while maintaining accuracy
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables precise 3D ego motion estimation and calibration, even in complex driving conditions, using multiple radar sensors to correct linear and angular velocities, providing a cost-effective alternative to ADMA sensors.
Implementation Method 1
the signals comprise position information and a radial velocity of each of at least three objects relative to the at least one sensor
Data Source
AI summary
A radar-based system in a vehicle for driver assistance or automated driving. The radar-based system includes a processor configured to: receive signals from at least one sensor of the vehicle configured to detect an object outside the vehicle, wherein the signals include position information and a radial velocity of each of at least three objects relative to the at least one sensor, and determine a velocity of the vehicle based on the received signals.