Vehicle Speed Estimation Using Radar Doppler Analysis
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Solution Overview
Problem
Conventional methods for estimating vehicle speed, such as using tire rotation and GPS, are inaccurate in various conditions like potholes, uneven tire inflation, or areas with poor GPS signals, necessitating redundant systems for reliable speed estimation, especially in autonomous and semi-autonomous vehicles.
Innovation Solution
The use of radar systems to generate speed estimates by fitting a cosine curve to data frames containing angular positions and measured velocities, with moving object velocities removed to improve accuracy, and combining multiple radar system estimates for enhanced reliability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional methods (tire rotation, GPS) are used for speed estimation, then the system is simple, but the measurement precision deteriorates under various conditions
Solution Approach 1:
The patent replaces mechanical speed estimation methods (tire rotation sensors) and GPS-based methods with a radar-based electromagnetic measurement system. The radar system uses Doppler effect to measure velocity directly, substituting mechanical and satellite-based systems with electromagnetic wave-based measurement, thereby improving accuracy independent of tire conditions or GPS signal availability.
Solution Approach 2:
The radar system serves multiple functions: it estimates vehicle speed, detects stationary objects, identifies moving objects, and provides data for both autonomous driving decisions and maintenance alerts. This multi-functionality improves measurement precision while managing system complexity through shared hardware infrastructure.
2Reliability
If redundant speed estimation systems are implemented, then the reliability improves, but the device complexity increases
Solution Approach 1:
The radar system provides multiple speed estimates through different processing methods (cosine curve fitting, stationary object detection, moving object removal) using the same hardware infrastructure. This achieves redundancy and improved reliability without proportionally increasing device complexity, as one radar system performs multiple measurement functions.
Solution Approach 2:
The system compares radar-based speed estimates with wheel-rotation-based speedometer readings to generate maintenance alerts. This feedback mechanism validates the radar system against conventional methods, improving reliability through cross-verification while using the existing speedometer infrastructure rather than adding completely redundant systems.
3Measurement precision
If radar-based speed estimation is used, then the measurement precision improves, but the device complexity increases compared to conventional methods
Solution Approach 1:
The patent replaces mechanical tire rotation sensors and GPS receivers with a radar system that uses electromagnetic waves and Doppler effect for speed measurement. This substitution improves measurement precision by eliminating dependencies on mechanical tire conditions and satellite signal availability, while the radar system's multi-functionality helps manage the complexity increase.
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
This approach provides a more accurate and redundant method for vehicle speed estimation, independent of tire conditions and GPS availability, ensuring optimal vehicle performance and safety in autonomous and semi-autonomous operations.
Implementation Method 1
The plurality of measured velocities comprise a measured velocity at each angular position of the plurality of angular positions
Implementation Method 2
receive data captured by a radar system on a vehicle
Data Source
AI summary
Systems, methods, and other embodiments relate to determining the speed of a vehicle. In one embodiment, a method includes receiving a first frame of data generated by a first sensor of a vehicle, the first frame of data including a first set of angular positions associated with a first set of objects in the environment. The method includes receiving a second frame of data generated by a second sensor of the vehicle, the second frame of data including a second set of angular positions associated with a second set of objects in the environment. The method includes generating a speed estimate for the vehicle in relation to the first set of objects and the second set of objects based at least in part on the first set of angular positions of the first frame of data and the second set of angular positions of the second frame of data.