Ultrasonic Sensor Object Classification via Temporal Differentiation
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Solution Overview
Problem
Current ultrasonic sensors in vehicles lack the ability to differentiate between dynamic and static objects, which is crucial for automated driving scenarios where the assumption of static objects is no longer valid.
Innovation Solution
A method using an ultrasonic sensor system that generates and detects sound signals to collect measurement data, forming two-dimensional arrays with time and distance information, and extracts echo traces to classify objects as static or dynamic based on relative speed calculations, without requiring Doppler effect measurements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If ultrasonic sensors are used for automated driving, then object detection capability is improved, but the ability to differentiate between static and dynamic objects deteriorates
Solution Approach 1:
The patent applies the dynamics principle by transforming static distance measurements into dynamic speed measurements through temporal differentiation. The system calculates relative speed by differentiating distance values over time, enabling the sensor system to detect and differentiate dynamic objects from static ones using the same ultrasonic sensor hardware.
Solution Approach 2:
The patent introduces time as an intermediary parameter to bridge the gap between distance measurement and motion detection. By measuring distance at multiple time points and calculating the rate of change, the system derives speed information that enables dynamic object differentiation without requiring additional sensors.
2Loss of information
If Doppler effect measurements are used to detect relative speed, then dynamic object differentiation is improved, but device complexity and cost increase
Solution Approach 1:
The patent uses a copying approach by replicating the existing ultrasonic distance measurement functionality to obtain speed information. Instead of introducing a completely new Doppler measurement system, the invention copies the distance measurement process multiple times over time and derives speed from the temporal changes, thereby avoiding additional hardware complexity.
Solution Approach 2:
The patent substitutes the mechanical/Doppler-based speed measurement system with a computational approach. Rather than using Doppler effect measurements that would require additional hardware complexity, the system replaces the physical measurement mechanism with mathematical differentiation of distance data, simplifying the overall sensor system.
3Measurement precision
If measurement data is collected over extended time periods to improve classification accuracy, then classification precision is improved, but response time and productivity deteriorate
Solution Approach 1:
The patent applies partial action by collecting measurement data for a limited, optimized time period rather than continuously. The system determines relative speed based on distance measurements taken over a defined time interval, which is sufficient for accurate classification without requiring excessive measurement time, thus maintaining responsive performance.
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 classification of static and dynamic objects, improving surrounding area sensing and automated driving behaviors, and can be implemented as a retrofit for existing ultrasonic systems, optimizing starting release times for automated vehicles.
Implementation Method 1
sound signals are generated by means of at least one sensor over a defined time period, emitted into the surrounding area and detected by the at least one sensor as sound echoes
Implementation Method 2
A relative speed of the detected sound echoes is acquired with respect to the at least one sensor using a derivative over time of the measurement data of the array
Data Source
AI summary
A method classifies dynamic or static objects in a surrounding area with a control device. Sound echoes are generated by at least one sensor over a defined time period. The sound echoes are emitted into the surrounding area, and are detected by the at least one sensor in order to acquire measurement data. The measurement data of the at least one sensor are received by the control device. The received measurement data are recorded in a two-dimensional array. At least one echo trace is extracted from the array. A relative speed of the detected sound echoes with respect to the at least one sensor is determined using a derivative over time of the measurement data of the array. The at least one echo trace is classified based on the determined relative speed.