Vehicle Radar Ghost Object Classification via Track Pairing
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Solution Overview
Problem
Vehicle radar systems face inaccuracies due to multipath reflections, where transmitted energy is deflected by one object and reflected back, causing detection of a ghost object at an incorrect location, leading to potential unnecessary vehicle operations like automatic braking.
Innovation Solution
A method and system that detect and classify tracks of objects in a radar system by identifying candidate pairs, applying criteria such as range difference, reflective surface shape, dynamics correlation, and incident angle to distinguish between true objects and ghost objects, ensuring only true object data is used for vehicle operation control.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If radar system detects all reflected energy, then detection coverage is improved, but false ghost object detections increase
Solution Approach 1:
The patent segments the detection problem by dividing objects into two categories: true objects and ghost objects. It implements separate tracking databases and classification mechanisms for each type, allowing the system to process and analyze reflections differently based on their origin, thereby maintaining detection coverage while eliminating false alarms from multipath reflections
Solution Approach 2:
The patent introduces an intermediary classification system that acts as a mediator between raw radar detections and vehicle control actions. This classification mechanism analyzes track patterns, dynamics, and geometric relationships to identify ghost objects before they trigger false vehicle responses, effectively filtering harmful detections while preserving true object information
2Loss of information
If radar system processes all detected objects, then information completeness is improved, but computational complexity increases
Solution Approach 1:
The patent divides the processing workload by creating separate track databases for true objects and ghost objects. This segmentation allows the system to apply different processing rules and criteria to each category, reducing the computational burden on the overall system while maintaining complete information about both object types
Solution Approach 2:
The patent applies partial processing by focusing computational resources on identifying and classifying ghost objects through specific criteria (dynamics matching, geometric relationships) rather than processing all detected objects uniformly. This selective approach reduces overall computational complexity while maintaining information completeness
3Reliability
If vehicle responds to all detected objects, then safety response is improved, but unnecessary operations increase
Solution Approach 1:
The patent introduces a classification intermediary between object detection and vehicle control that filters out ghost objects before they can trigger unnecessary vehicle operations. This intermediary layer maintains safety responses to true objects while preventing false alarms from multipath reflections, thereby improving reliability by reducing unnecessary operations
Solution Approach 2:
The patent converts the harmful effect of multipath reflections into a beneficial classification opportunity. By analyzing the characteristic patterns of ghost object reflections (such as geometric relationships with true objects and inconsistent dynamics), the system transforms what was previously harmful noise into useful information for improving safety response 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
Accurately differentiates between true and ghost objects, reducing false alarms and improving vehicle operation by correlating ghost objects with their true counterparts, allowing for more precise velocity estimation of true objects.
Implementation Method 1
radio detection and ranging (radar) systems
Implementation Method 2
transmitted energy is reflected by an object in the field of view of the radar system
Implementation Method 3
When transmitted energy is deflected by one object to a second object, the reflected energy received from the second object is referred to as a multipath reflection
Data Source
AI summary
Systems and methods involve detecting objects using a radar system of a vehicle. Tracks of the objects are initiated in a track database. The tracks store data, respectively, for the objects and are updated based on additional detections of the objects. The tracks of the objects are initially unclassified tracks. Two tracks corresponding to two of the objects are selected as a candidate pair. Criteria are applied to the candidate pair to determine whether one track is of a ghost object and another track is of a true object corresponding with the ghost object. The ghost object represents detection of the true object in an incorrect location. The candidate pair is classified as tracks of a true object and ghost object pair based on determining that the one track is of the ghost object and the other track is of the true object corresponding with the ghost object.