Automotive Radar Sensor Fast Blockage Detection Method
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Solution Overview
Problem
Existing automotive radar systems take too long to detect sensor blockages due to reliance on statistical methods that require large amounts of data, leading to delayed confirmation of performance changes, which can impact safety in automatic driving assistance systems.
Innovation Solution
A method that collects and analyzes information on detected targets and objects within a split time window to determine performance indicators, allowing for quick detection of fast total blockage events by identifying typical and untypical detection performance, and object deletion rates, thereby reducing reaction time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If statistical methods are used to determine blockage status, then measurement precision is improved, but loss of time increases
Solution Approach 1:
The time window is divided into three distinct partitions (first, second, and third partitions) to analyze detection performance at different stages. This segmentation allows the system to compare performance across time periods and quickly identify sudden blockage events by detecting significant deviations between partitions, thereby reducing reaction time while maintaining detection accuracy.
Solution Approach 2:
Instead of requiring complete statistical analysis over long periods, the method uses performance indicators that evaluate only specific portions of the detection data (partitions of the time window). This partial action approach enables rapid blockage detection by focusing on critical time segments rather than processing entire historical datasets, thus reducing loss of time while preserving measurement precision.
2Reliability
If complex statistical methods are used to confirm performance changes, then reliability is improved, but device complexity increases
Solution Approach 1:
The patent replaces complex statistical analysis mechanisms with a simpler performance indicator-based evaluation system. Instead of using sophisticated statistical models that require extensive computation, the method uses straightforward comparisons of detection performance indicators across time window partitions. This substitution maintains reliability by detecting actual performance deviations while significantly reducing algorithmic complexity.
Solution Approach 2:
The method changes the approach from analyzing raw detection data with complex statistics to evaluating specific performance indicators (such as detection counts or confidence metrics) across time partitions. By transforming the problem into parameter comparison rather than full statistical analysis, the system achieves reliable blockage detection with simpler computational requirements, thus reducing device complexity while maintaining reliability.
Data Source
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AI summary
The invention provides a ethod for detecting fast total blockage of a sensor, comprising the steps of collecting and storing information concerning the numbers of targets and objects detected by the sensor, the number of objects created, and the number of objects lost within the detection field of the sensor in each detection cycle over a predetermined time window (T), splitting the time window (T) into a first partition (R), a second partition (O), and third partition (D), determining a first performance indicator based on the number of targets detected in the first partition (R) of the time window (T), a second performance indicator based on the number of targets detected in the third partition (D) of the time window (T), and a degradation indicator based on the number of objects lost within the detection field of the sensor during the second partition (O) of the time window (T); and determining that a fast total blockage event has happened if the first performance indicator shows detection performance typical for the sensor, the degradation indicator shows a fast degradation of detection performance, and the second performance indicator shows detection performance untypical for the sensor.