Vehicle Velocity Estimation Using Radar Stationary Object Data
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing vehicle motion estimation techniques are not optimal, particularly when the vehicle is not in a steady state condition, such as on a surface with a low coefficient of friction, which can affect the accuracy of velocity estimation for active safety features.
Innovation Solution
A method and system utilizing radar data from stationary objects to estimate vehicle motion, incorporating radar sensors and a processor to calculate velocity, even in non-steady state conditions, by combining data from radar sensors, yaw sensors, wheel speed sensors, and inertial measurement units with dynamic models.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional motion estimation techniques are used, then the system is simple to operate, but the measurement precision deteriorates in non-steady state conditions
Solution Approach 1:
The patent combines radar sensor data with inertial measurement unit data to create a hybrid motion estimation system. The radar sensor provides external reference measurements of stationary objects, while the IMU provides vehicle motion data. By merging these data sources through a calibration process that correlates radar-derived velocity with IMU-derived velocity, the system achieves accurate velocity estimation in non-steady state conditions where traditional methods fail.
Solution Approach 2:
The patent introduces a calibration module as an intermediary that processes and correlates data from the radar sensor and IMU. This calibration module acts as a mediator that transforms raw radar measurements into calibrated velocity estimates by comparing them with IMU data and applying calibration factors. This intermediary processing layer enables the system to achieve high measurement precision without requiring direct complex hardware integration.
2Measurement precision
If radar data from stationary objects is used, then the measurement precision improves in non-steady state conditions, but the device complexity increases
Solution Approach 1:
The radar sensor serves multiple functions: it detects stationary objects for motion estimation, provides calibration data for the IMU, and can potentially be used for other vehicle safety functions. The patent leverages the universal capability of the radar sensor to perform both calibration and measurement tasks, reducing the need for dedicated separate systems and thereby managing complexity while maintaining high precision.
Solution Approach 2:
The system uses the radar sensor to self-calibrate the IMU by providing external reference measurements of stationary objects. The calibration process is performed automatically by the system itself without requiring external intervention or additional calibration equipment. The radar data serves the dual purpose of both calibration reference and operational measurement, enabling the system to self-service its own accuracy requirements.
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
Enhances the accuracy of vehicle motion estimation, particularly on low-friction surfaces, by providing reliable velocity estimates for active safety features like automatic braking and steering assist, improving safety and control systems.
Implementation Method 1
one or more radar sensors are configured to at least facilitate obtaining radar data pertaining to one or more stationary objects in proximity to the vehicle
Data Source
AI summary
Methods and systems for estimating motion of a vehicle are provided. Radar data pertaining to one or more stationary objects in proximity to the vehicle are obtained via one or more radar units of the vehicle. The motion of the vehicle is estimating using the radar data via a processor of the vehicle.