Radar Object Detection Using Dynamic Threshold Adjustment
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Solution Overview
Problem
Existing drive assist systems frequently lose detection of objects with low radio wave intensity, leading to erroneous control and unnecessary acceleration/deceleration, and are prone to false warnings due to threshold setting issues.
Innovation Solution
An object detection system using a radar with dual threshold values and optional image recognition to differentiate between objects with high and low detection probability, preventing erroneous detection and loss of detected objects by adjusting threshold settings based on past and current radio wave intensity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a higher threshold value is set for identifying vehicles, then erroneous detection is reduced, but objects with low radio wave intensity are frequently lost
Solution Approach 1:
The patent applies dynamics by making the threshold value adjustable rather than fixed. The object determination section dynamically selects between a first threshold value and a second threshold value based on the detection history and probability of object existence. This allows the system to adapt the threshold to current detection conditions, resolving the contradiction between preventing erroneous detection and avoiding loss of low-intensity objects.
Solution Approach 2:
The patent changes the parameter of threshold value based on detection probability and history. When an object's existence probability is high (detected in past frames), the system uses a lower second threshold value to maintain detection. When probability is low, it uses a higher first threshold value to prevent false detections. This parameter change strategy resolves the contradiction by adapting the threshold to the specific detection context.
2Measurement precision
If a lower threshold value is set for identifying vehicles, then objects with low radio wave intensity are detected, but erroneous detection and false warnings increase
Solution Approach 1:
The system dynamically adjusts the threshold value based on the object's detection history and existence probability. For objects with high detection probability (detected in previous frames), the system applies a lower second threshold value to ensure continuous detection. For objects with low probability, a higher first threshold value is used to prevent false warnings. This dynamic adjustment resolves the contradiction between detecting low-intensity objects and preventing erroneous detection.
Solution Approach 2:
The patent implements parameter changes by selecting different threshold values (first threshold value vs. second threshold value) based on the detection probability determined from past detection results. This allows the system to optimize the threshold parameter for each specific detection scenario, achieving both high detection accuracy and low false warning rates.
3Ease of operation
If a single threshold value is used for all objects, then the system is simple to operate, but it cannot adapt to different object types and detection conditions
Solution Approach 1:
The patent segments the detection process by dividing objects into two categories based on detection probability: objects with high existence probability (detected in past frames) and objects with low existence probability. Each category uses a different threshold value (second threshold value for high probability, first threshold value for low probability). This segmentation allows the system to maintain simple operation while achieving adaptability to different detection conditions.
Solution Approach 2:
The system dynamically determines which threshold value to apply based on the object's detection history and existence probability calculated by the object determination section. This dynamic selection process maintains ease of operation (the system automatically selects thresholds) while achieving adaptability to different object types and detection scenarios without requiring manual threshold configuration.
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 reduces erroneous detection and loss of objects with low radio wave intensity, enhancing the accuracy and reliability of object detection and control in drive assist systems.
Implementation Method 1
a first object detection unit for detecting an object in an area near the system using a radar
Data Source
AI summary
An object detection system includes a first object detection unit that detects an object in an area near the system using a radar and an object determination section that determines whether the object in the area near the system is a subject of detection, using a result of detection by the first object detection unit. The object determination section treats the object as the subject of detection if (i) an intensity of a radio wave from the object that is currently received by the first object detection unit is equal to or higher than a first threshold value or if (ii) an intensity of a radio wave from the object that was received in the past by the first object detection unit was equal to or higher than the first threshold value and the intensity of the radio wave from the object that is currently received by the first object detection unit is equal to or higher than a second threshold value that is lower than the first threshold value.