Velocity Estimation Using Characteristic Frequency
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Solution Overview
Problem
Existing methods for estimating the velocity of objects, such as vehicles or people, are limited in accuracy and reliability, particularly when using inertial signals from accelerometers, as they often fail to account for coupled movements and rotational accelerations effectively.
Innovation Solution
The use of accelerometer signals to determine a characteristic frequency through frequency spectrum analysis or model application, allowing for the estimation of velocity by multiplying the characteristic frequency with a proportionality factor, which can include wheel radius for wheeled vehicles, and incorporating sensor fusion with additional sensor signals for improved accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If accelerometer signals are used to estimate velocity, then velocity estimation can be performed without GPS or radar, but the accuracy and reliability of velocity estimation deteriorates due to failure to account for coupled movements and rotational accelerations
Solution Approach 1:
The patent segments the acceleration measurement into two distinct components: translational acceleration (from the first accelerometer in the vehicle) and rotational acceleration (from the second accelerometer in the wheel). By separating these coupled movements into independent measurement channels, the system can accurately distinguish between linear motion and rotational motion, thereby resolving the accuracy problem while maintaining the versatility of accelerometer-based velocity estimation.
2Device complexity
If only translational acceleration is measured, then the measurement system remains simple, but the velocity estimation becomes unreliable when rotational movements are present
Solution Approach 1:
The patent introduces a processing unit as an intermediary that receives acceleration signals from both the vehicle-mounted accelerometer and the wheel-mounted accelerometer. This intermediary component performs the critical function of separating translational and rotational acceleration components through signal processing, enabling reliable velocity estimation without requiring complex mechanical coupling between the sensors.
3Ease of operation
If coupled movements are not accounted for, then the velocity estimation process remains straightforward, but the results become inaccurate in scenarios with rotational acceleration
Solution Approach 1:
The patent performs preliminary separation of translational and rotational acceleration components before conducting velocity estimation. By pre-processing the acceleration signals to isolate the translational component (which directly relates to vehicle velocity) from the rotational component, the system maintains a straightforward velocity estimation process while ensuring accurate results even in the presence of rotational movements.
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 enhances the accuracy of velocity estimation by accounting for both translational and rotational movements, reducing uncertainty and increasing reliability, especially in scenarios where objects are coupled or partially coupled, and enables applications in navigation and localization systems.
Implementation Method 1
accelerometer signals, which indicate an acceleration of a first object and/or a second object
Implementation Method 2
a frequency spectrum analysis may be performed on the accelerometer signals to obtain an accelerometer signal spectrum
Data Source
AI summary
The present disclosure relates to the estimation of a velocity of a first object using accelerometer signals, indicating an acceleration of the first object and/or a second object coupled to a first object. To this end, a characteristic frequency in the accelerometer signal spectrum may be determined, preferably by applying a parametric model or by performing a spectrum analysis, and used as a basis to estimate the velocity of the first object based on the determined characteristic frequency. The characteristic frequency may be determined by identifying the frequency having the maximum spectral amplitude or by identifying the fundamental frequency or a particular harmonic in the spectrum.