Object Detection With Adaptive CFAR Thresholds for Road Clutter
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Solution Overview
Problem
Existing object detection systems using CFAR processing struggle to accurately distinguish between reception waves reflected by detection targets and clutter due to varying clutter levels based on environmental conditions, particularly road surface states.
Innovation Solution
The object detection device employs dynamic threshold setting in CFAR processing, utilizing CA-CFAR and GO-CFAR techniques to adjust thresholds based on environmental variations, combined with road surface estimation to minimize clutter interference.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a fixed threshold is used in CFAR processing, then the detection system is simple and easy to operate, but detection accuracy deteriorates when clutter levels vary due to environmental conditions
Solution Approach 1:
The patent applies dynamics by transitioning from a fixed threshold to a dynamic threshold that automatically adapts to varying clutter levels. The threshold is calculated based on the standard deviation of the received signal, allowing it to change dynamically according to environmental conditions such as road surface state, while maintaining ease of operation through automated adjustment.
Solution Approach 2:
The patent changes the threshold parameter from a fixed value to a variable value that depends on the standard deviation of the received signal. By making the threshold a function of the signal's statistical properties, the system maintains high detection accuracy across different environmental conditions without requiring manual intervention.
2Object-affected harmful factors
If the threshold is set high to avoid clutter detection, then clutter reduction is improved, but detection of legitimate targets may be lost
Solution Approach 1:
The patent implements feedback by using the standard deviation of the received signal to dynamically adjust the threshold. The threshold is calculated based on the actual signal characteristics, creating a feedback loop where the system continuously adapts to maintain optimal detection performance. This ensures that high clutter environments do not cause unnecessary detections while maintaining reliable target detection.
Solution Approach 2:
The patent changes the threshold parameter dynamically based on the standard deviation of the received signal. When clutter levels are high (large standard deviation), the threshold increases to avoid clutter detection. When clutter levels are low (small standard deviation), the threshold decreases to maintain sensitive target detection, thus balancing clutter reduction with target detection reliability.
3Object-affected harmful factors
If CFAR processing is applied to reduce clutter, then clutter reduction is improved, but detection precision deteriorates when environmental conditions cause varying clutter levels
Solution Approach 1:
The patent applies dynamics by making the CFAR processing adaptive through dynamic threshold adjustment. Instead of using a fixed threshold that performs poorly in varying environmental conditions, the system dynamically adjusts the threshold based on the standard deviation of the received signal, maintaining high detection precision across different clutter levels while effectively reducing clutter.
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 allows for accurate detection of reception waves from detection targets while effectively reducing clutter, ensuring reliable object detection regardless of environmental conditions.
Implementation Method 1
a reception wave as a transmission wave reflected by and returned from an object
Data Source
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AI summary
An object detection device (200, 201, 202, 203, 204) includes: a transmission unit (411) transmitting a first transmission wave; a reception unit (421) receiving a first reception wave reflected by an object; a signal processing unit (426) sampling a first processing target signal according to the first reception wave and acquiring a difference signal based on a difference between the first processing target signal for at least one sample at a certain detection timing, and the first processing target signal for a plurality of samples in at least one of first and second periods; a threshold setting unit (428) setting a threshold as a comparison target with the value of the difference signal, based on variation in the values of the first processing target signal for the plurality of samples; and a detection unit (429) detecting information about the object at the detection timing based on a comparison result between the value of the difference signal and the threshold.