Automotive Radar Blockage Detection via Static Infrastructure Reflections
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Solution Overview
Problem
Existing radar blockage detection solutions in vehicle radar systems are limited by their slow detection speed and accuracy, often resulting in false reports due to variations in signal strength and environmental conditions, making it difficult to quickly and reliably identify antenna blockages caused by foreign matter accumulation.
Innovation Solution
The use of reflections from static infrastructure, such as curbs and trees, to generate a Doppler Monopulse Image (DMI) that rapidly forms upon vehicle startup, allowing for immediate blockage detection and improving accuracy over time by analyzing the 'clutter ridge' signature, which distinguishes it from noise, and providing signals to the Controller Area Network (CAN) and human/machine interface (HMI) for alerting purposes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If statistics from passing objects are used for blockage detection, then blockage detection capability is provided, but detection speed is slow requiring several minutes of data gathering
Solution Approach 1:
The system performs preliminary actions by using reflections from static infrastructure (curbs, trees, guardrails) that are continuously present during vehicle operation. These reflections are captured and processed to form a Doppler Monopulse Image (DMI) that rapidly develops within seconds, providing immediate blockage detection capability without requiring several minutes of data gathering from passing objects.
Solution Approach 2:
The patent introduces an intermediary approach by using static infrastructure reflections as a mediator between the radar sensor and moving targets. Instead of relying solely on statistics from passing objects, the system uses the consistent reflections from stationary infrastructure elements to create a reference framework (DMI with clutter ridge) that enables faster and more reliable blockage detection.
2Reliability
If statistics from passing objects are used for blockage detection, then blockage detection is enabled, but accuracy is limited due to signal strength variations from target size, shape, and environmental factors
Solution Approach 1:
The system applies homogeneity by using reflections from static infrastructure that provide consistent and uniform signal characteristics. Unlike passing objects that vary in size, shape, and reflectivity, static infrastructure elements (curbs, trees, guardrails) provide homogeneous reflection patterns that form a stable clutter ridge in the DMI, enabling more accurate blockage detection不受target variations.
Solution Approach 2:
Static infrastructure reflections serve as an intermediary reference that mediates between the radar sensor and variable passing objects. The clutter ridge formed by these consistent reflections provides a stable baseline against which blockage can be accurately detected, eliminating the accuracy limitations caused by target size, shape, and environmental variations.
3Measurement precision
If data gathering time is extended to improve algorithm accuracy, then false blockage reports are reduced, but detection speed decreases
Solution Approach 1:
The system performs preliminary action by continuously capturing and processing reflections from static infrastructure during normal vehicle operation. The Doppler Monopulse Image (DMI) is rapidly formed within seconds of startup using these pre-captured reflections, enabling immediate blockage detection without requiring extended data gathering periods to improve algorithm accuracy.
Solution Approach 2:
The patent implements continuity of useful action by continuously capturing reflections from static infrastructure throughout vehicle operation. This continuous data accumulation from persistent infrastructure elements allows the DMI to rapidly develop and provides ongoing accurate blockage detection capability without the need to extend detection time, maintaining both high speed and high accuracy.
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 enables faster and more accurate detection of radar sensor blockages, reducing the time required for detection and minimizing false reports by leveraging static infrastructure reflections to improve sensor performance and reliability.
Implementation Method 1
generating a plot of normalized Doppler versus monopulse angle
Implementation Method 2
use reflections from static infrastructure (e.g., reflections from curb, grass, guardrail, bushes, trees, cracks in the road, etc.)
Data Source
Figure 1a
Figure 1b
Figure 2
AI summary
A radar sensor for use within a vehicle includes blockage detection functionality. In at least one embodiment, the radar sensor collects information on stationary infrastructure around the vehicle. The infrastructure information may be used to generate a Doppler Monopulse Image (DMI) or other graph for the sensor. A clutter ridge within the DMI or other graph may be analyzed determine a blockage condition of the sensor (i.e., unblocked, partially blocked, or fully blocked).