Adaptive Threshold Object Detection Using Low-Pass Filtered Pulse Waves
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Solution Overview
Problem
Existing object detection systems face challenges in suppressing the influence of road surface reflection noise while maintaining detection performance and avoiding cost increases, particularly due to the requirement for onboard cameras and assumptions of worst-case conditions.
Innovation Solution
An object detection apparatus that transmits and receives pulse waves, utilizing a low-pass filter to differentiate between object and road surface reflections, calculates an adaptive threshold based on the filtered output, allowing for accurate object detection without the need for a camera, thus reducing costs and noise interference.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a camera is used to image the road surface for determining noise removal threshold, then the noise removal accuracy is improved, but the system cost increases
Solution Approach 1:
The patent extracts and removes the camera component from the system, replacing it with a threshold calculation unit that processes reflected wave signals directly. This eliminates the need for separate road surface imaging hardware while maintaining noise removal effectiveness through signal-based threshold determination.
Solution Approach 2:
The reflected wave receiving unit serves multiple functions: it both detects objects and provides data for threshold calculation. The same received signal is used for both object detection and adaptive threshold determination, eliminating the need for separate camera hardware dedicated to road surface imaging.
2Reliability
If a worst-case condition threshold is set for noise removal, then the reliability is improved, but the object detection performance decreases
Solution Approach 1:
The threshold is made dynamic and adaptive rather than fixed. The threshold calculation unit continuously adjusts the noise removal threshold based on the actual characteristics of the received reflected wave signals, allowing the system to adapt to varying road surface conditions and maintain optimal detection performance.
Solution Approach 2:
The system uses feedback from the received reflected wave signals to automatically adjust the threshold. The threshold calculation unit analyzes the actual signal characteristics and modifies the threshold accordingly, creating a closed-loop system that balances noise removal reliability with detection 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
The system effectively suppresses road surface reflection noise in object detection while maintaining performance and reducing costs by calculating an adaptive threshold using the filtered output, enabling reliable object detection without the need for an onboard camera.
Implementation Method 1
a filter that passes, among the received reflected wave, only frequencies that are at least smaller than a pulse frequency of the probe wave
Implementation Method 2
transmits and receives pulse probe wave such as ultrasonic wave and electromagnetic wave to detect an object existing in a probe wave illumination range
Implementation Method 3
receives a reflected wave of the probe wave
Data Source
AI summary
An object detection apparatus mounted to a vehicle includes a transmitter, a receiver, a filter, a threshold calculator, and an object determinator. The transmitter transmits a probe wave in pulse form. The receiver receives a reflected wave of the probe wave. The filter passes, among the received reflected wave, only frequencies that are at least smaller than a pulse frequency of the probe wave. Based on an output of the filter, the threshold calculator calculates an objection determination threshold for determining presence and absence of an object. The object determinator determines the presence and absence of the object by using the objection determination threshold calculated by the threshold calculator.