Vehicle Radar Reflection Filtering via Geometric Analysis
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Solution Overview
Problem
Radar systems in vehicles face challenges in distinguishing self-reflections from actual objects, leading to potential undesirable actions such as braking or swerving due to ghost vehicles detected in radar data.
Innovation Solution
The implementation of radar reflection filtering techniques using vehicle sensors to identify and filter self-reflections by determining the geometric relationship between the vehicle, detected objects, and potential ghost objects, thereby adjusting the reflection filter to reduce false detections.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If radar systems detect all reflected signals, then detection coverage is improved, but false detections from self-reflections increase
Solution Approach 1:
The patent segments the detection process by separating self-reflection detection from actual object detection. It identifies self-reflections as distinct entities and applies specific filtering criteria (geometric relationships, velocity patterns, signal characteristics) to segment and remove them from the detection results, thereby improving overall detection accuracy while reducing false positives
Solution Approach 2:
The patent introduces intermediate processing steps between raw radar signal reception and final object detection. These intermediate filters act as mediators that analyze geometric relationships between the vehicle, detected objects, and potential self-reflections, using velocity information and spatial constraints to mediate between raw data and reliable detections
2Reliability
If radar filtering is applied to remove self-reflections, then false detections are reduced, but detection of actual objects may be affected
Solution Approach 1:
The patent implements feedback mechanisms where detection results are continuously analyzed and filtered based on geometric relationships and velocity information. The system provides feedback loops that adjust filtering criteria based on the detected patterns, allowing it to distinguish between self-reflections and actual objects dynamically, thereby maintaining high reliability without sacrificing detection accuracy
Solution Approach 2:
The patent changes multiple parameters simultaneously to identify self-reflections: spatial parameters (geometric relationships between vehicle, object, and reflection), temporal parameters (velocity patterns over time), and signal parameters (Doppler shifts, signal strength). By monitoring multiple parameters together, the system can reliably filter self-reflections while preserving actual object detections
3Reliability
If multiple sensors are used to verify object detection, then detection reliability is improved, but system complexity increases
Solution Approach 1:
The patent makes the radar system multi-functional by enabling it to perform both primary object detection and self-reflection identification using the same sensor. By analyzing geometric relationships and velocity patterns from the same radar data, the system achieves verification functionality without adding separate sensors, thereby improving reliability while controlling complexity
Solution Approach 2:
The radar system serves itself by using its own detected data to identify and filter its own false detections. The system analyzes its detection results for patterns characteristic of self-reflections (such as specific geometric relationships and velocity patterns) and automatically filters them, providing self-verification without requiring external sensors or additional system complexity
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 effectively reduces the frequency of undesirable control actions by accurately distinguishing self-reflections from actual objects within radar data, enhancing the reliability of sensor data and improving vehicle navigation safety.
Implementation Method 1
Radio detection and ranging systems ('radar systems') are used to estimate distances to environmental features by emitting radio signals and detecting returning reflected signals
Implementation Method 2
Some radar systems may also estimate relative motion of reflective objects based on Doppler frequency shifts in the received reflected signals
Data Source
AI summary
Example embodiments relate to radar reflection filtering using a vehicle sensor system. A computing device may detect a first object in radar data from a radar unit coupled to a vehicle and, responsive to determining that information corresponding to the first object is unavailable from other vehicle sensors, use the radar data to determine a position and a velocity for the first object relative to the radar unit. The computing device may also detect a second object aligned with a vector extending between the radar unit and the first object. Based on a geometric relationship between the vehicle, the first object, and the second object, the computing device may determine that the first object is a self-reflection of the vehicle caused at least in part by the second object and control the vehicle based on this determination.