Radar Blindness Detector Using Multi-Sensor Probability
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Solution Overview
Problem
Conventional radar sensors face challenges in accurately detecting blindness or blockage, leading to false alarms due to environmental conditions, such as lack of returning signals in empty environments, which can result in unreliable obstacle identification.
Innovation Solution
A radar blindness and blockage detector system that utilizes additional sensor data and external information to calculate a probability indicator for radar sensor blockage, integrating data from sensors like optical, ultrasonic, and weather sensors, and cloud services to adapt filter parameters and thresholds, thereby improving detection reliability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If radar sensor monitors properties of returned radar signals to detect blockage, then blockage detection capability is provided, but false alarms occur in empty environments where no objects are present
Solution Approach 1:
The patent combines radar sensor data with data from additional sensors (optical sensors, ultrasonic sensors, weather sensors) to perform blockage detection. By merging multiple sensor inputs, the system can distinguish between actual blockages and environmental conditions that mimic blockages, thereby reducing false alarms while maintaining detection capability.
Solution Approach 2:
The processing device acts as an intermediary that receives and evaluates data from multiple sensors before determining blockage status. This intermediary layer processes the information from different sensor types and external data sources to calculate a probability indicator, preventing direct and potentially erroneous blockage declarations from single sensor inputs.
2Productivity
If radar sensor operates in environments with no surrounding objects, then radar signal transmission continues, but blockage is falsely detected due to lack of returning signals
Solution Approach 1:
The system uses feedback from multiple sensors to continuously evaluate whether the radar sensor is actually blocked or simply operating in an environment with no reflective objects. The processing device receives ongoing data from optical, ultrasonic, and weather sensors to adjust blockage determination dynamically, preventing false detections during normal operation in empty environments.
Solution Approach 2:
The system changes the parameters used for blockage detection by incorporating multiple sensor types and external data sources rather than relying solely on radar signal properties. This multi-parameter approach allows the system to distinguish between genuine blockages and environmental conditions, improving measurement precision while maintaining productivity.
3Reliability
If additional sensor data and external information are integrated to calculate probability indicator, then detection reliability is improved, but device complexity increases
Solution Approach 1:
The processing device is designed with multi-functionality to handle data from multiple sensor types and external data sources. By creating a universal processing platform that can evaluate diverse inputs through a unified probability calculation approach, the system improves reliability without proportionally increasing complexity, as the same processing architecture handles all sensor inputs.
Data Source
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AI summary
Detection of a blind or blocked radar sensor. For this purpose, it is proposed to refer to sensor data from one or more further sensors and/or to data from external data sources. Based on this additional data, a probability or likelihood for a blind or blocked radar sensor is calculated and the final decision for a blind or blocked radar sensor is performed by evaluating the blockage detection of the radar sensor itself in combination with the calculated probability for a blind or blocked radar sensor. In this way, false detections of blind or blocked radar sensors can be reduced and the reliability of a blindness or blockage detection of a radar sensor can be improved.