Radar and Night Vision Fusion for Obstacle Identification
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Solution Overview
Problem
Current vehicle obstacle identification systems face challenges in reliably detecting objects, especially those with weak radar signatures, leading to potential accidents or false alarms, which can impair vehicle operation and safety.
Innovation Solution
A method and system combining radar sensors and night vision cameras for obstacle identification, where both detection techniques verify each other to reduce false positives and ensure reliable detection, with the radar sensor using radio frequency signals and the night vision camera utilizing visible and IR light to confirm obstacle presence.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If radar sensors are used to detect obstacles, then detection range and speed are improved, but detection reliability deteriorates for objects with weak radar signatures
Solution Approach 1:
The patent combines radar sensors and night vision cameras into a fused sensor system. The radar provides fast detection with broad coverage, while the night vision camera provides reliable visual confirmation. The control unit fuses data from both sensors to produce accurate obstacle identification, resolving the contradiction between fast detection and reliable detection.
2Measurement precision
If radar sensitivity is increased to detect weak signatures, then detection capability is improved, but false alarm rate increases
Solution Approach 1:
The system uses feedback from the night vision camera to verify radar detections. When the radar detects a potential obstacle with weak signature, the control unit uses the camera image to confirm or refute the detection. This feedback mechanism allows the radar to operate at high sensitivity without increasing false alarms, as the camera provides verification.
3Reliability
If multiple sensors are combined for verification, then detection reliability is improved, but system complexity increases
Solution Approach 1:
The control unit serves multiple functions: it processes radar data, processes camera data, fuses the two data streams, and generates control signals. This multi-functionality reduces the need for separate dedicated processing units for each sensor type, thereby reducing overall system complexity while maintaining high detection reliability through sensor fusion.
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 enhances obstacle detection reliability while minimizing false alarms, allowing for accurate identification of potential hazards even under low light conditions, thereby improving vehicle safety and preventing accidents.
Implementation Method 1
a first obstacle search is performed with a radar sensor using a radio frequency signal
Implementation Method 2
The radar sensor transmits a radar signal, which could be a continuous wave or a pulse signal, and receives a reflected signal
Implementation Method 3
The night vision camera is adapted for operation at low light levels. It may use amplification of the visible light, detection of (near) IR light or a combination of both to generate an image
Data Source
AI summary
A method for obstacle identification for a vehicle. In order to provide means for reliable obstacle identification for a vehicle, the method includes: performing a first obstacle search with a radar sensor using a radio frequency signal; performing a second obstacle search with a night vision camera; and identifying an obstacle if a first detection of the first obstacle search corresponds to a second detection of the second obstacle search, wherein a reliability of the first detection is assessed and if the reliability is above a first threshold, the obstacle is identified independently of the second obstacle search.