On-Vehicle Radar Reflection Comparison for Abnormality Detection
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Solution Overview
Problem
Conventional radar systems face challenges in accurately determining abnormalities due to varying road surface reflection intensities, leading to erroneous determinations or delayed detection, as they rely on threshold settings and statistical processing that can be unreliable.
Innovation Solution
An on-vehicle object detection system that compares road surface reflection levels between multiple radar apparatuses to identify abnormalities by calculating differences exceeding predefined values, allowing for early and accurate detection without complex statistical processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a low threshold is set for abnormality determination, then abnormality detection sensitivity is improved, but erroneous determination increases due to road surface reflection variations
Solution Approach 1:
The system divides the abnormality detection task into multiple independent radar apparatuses (first radar and second radar) that separately measure road surface reflection levels. By segmenting the measurement function across multiple devices, the system can compare results to distinguish true abnormalities from normal variations, thereby improving determination accuracy while maintaining detection sensitivity.
2Reliability
If statistical processing over long time periods is performed, then erroneous determination is reduced, but abnormality detection is delayed
Solution Approach 1:
The system performs preliminary comparative measurement using multiple radar apparatuses to establish a reference for normal reflection level variations. By having multiple radars simultaneously measure and compare road surface reflection levels in real-time, the system creates a baseline understanding of normal variations without requiring long-term statistical accumulation, thus enabling timely abnormality detection.
Solution Approach 2:
The system continuously compares road surface reflection levels from multiple radar apparatuses and provides feedback when differences exceed a predetermined threshold. This real-time feedback mechanism allows the system to immediately identify abnormalities without waiting for long-term statistical processing, reducing detection time while maintaining accuracy through continuous monitoring and comparison.
3Reliability
If multiple radar apparatuses are used for comparison, then determination accuracy is improved, but device complexity increases
Solution Approach 1:
The multiple radar apparatuses used in the system are designed with universal functionality, serving both as object detection devices and as road surface reflection level measurement devices. This multi-functionality allows the system to achieve improved determination accuracy through comparison without adding dedicated complexity, as the same hardware performs multiple functions.
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 reduces erroneous determinations and enables early identification of radar apparatus abnormalities by comparing reflection levels across multiple sensors, enhancing reliability and accuracy in abnormality detection.
Implementation Method 1
a radar apparatus provided with a processing device that detects the position of an object to be detected, on the basis of a transmission signal from radar beam transmission means and a reception signal from reception means
Implementation Method 2
the reflection intensity of a road surface changes depending on the state of the road surface
Data Source
AI summary
The difference between a plurality of road surface reflection levels detected by a plurality of object detection apparatuses mounted to a vehicle is calculated, and when the difference exceeds a range of values determined in advance, a control apparatus determines that there is an abnormality in any of the plurality of object detection apparatuses. Accordingly, without causing statistical processing to be complicated, occurrence of an abnormality in the object detection apparatus can be determined less erroneously than before.