Radar Object Tracking Freezing for False Motion Reduction
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Solution Overview
Problem
Radar sensors face limitations in accuracy and reliability when detecting objects at low speeds or when both the object and the host vehicle are stationary, leading to ambiguous detections and false motion readings.
Innovation Solution
A system that determines if a tracked object is near a host vehicle and classifies it as frozen relative to stationary ground when its velocity and the host vehicle's speed are below specific thresholds, freezing the object's position to prevent false motion detection and updating only relevant state variables periodically.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If radar tracking continues updating object position at low speeds or stationary conditions, then tracking coverage is maintained, but false motion detection increases and measurement accuracy deteriorates
Solution Approach 1:
The system dynamically adjusts the tracking update behavior based on detected motion conditions. When an object is classified as frozen (stationary), the system freezes the position tracking to prevent false motion detection. When motion is detected, normal tracking resumes. This dynamic adaptation resolves the contradiction by making the tracking system flexible rather than static.
Solution Approach 2:
The system changes the tracking parameter state by introducing a 'frozen' classification state. When velocity thresholds are exceeded or object distance changes significantly, the system transitions from frozen to active tracking. This parameter change allows the system to maintain reliability during stationary conditions while preserving measurement precision when motion occurs.
2Productivity
If radar continuously tracks all detected objects, then complete monitoring is achieved, but computational resources are wasted on stationary objects causing system complexity to increase
Solution Approach 1:
The system extracts stationary objects from the active tracking pipeline by classifying them as frozen. These frozen objects are removed from continuous update cycles, requiring computational resources only when they transition to motion. This extraction principle improves productivity by eliminating unnecessary processing while maintaining the ability to detect when these objects become relevant again.
Solution Approach 2:
Instead of continuous tracking updates for all objects, the system implements periodic checks to detect transitions from frozen to moving state. The system periodically evaluates velocity thresholds and distance changes, updating tracking status only when necessary. This periodic action reduces computational burden while maintaining effective monitoring of stationary objects.
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 enhances the accuracy of object tracking by reducing false motion detection and maintaining accurate information about stationary objects, improving the reliability of driver assistance and autonomous vehicle systems.
Implementation Method 1
radar tracking devices may provide information regarding objects in a vicinity or pathway of a vehicle
Data Source
AI summary
An illustrative example method of tracking a detected object comprises determining that a tracked object is near a host vehicle, determining an estimated velocity of the tracked object, and classifying the tracked object as frozen relative to stationary ground when the estimated velocity is below a preselected object threshold and a speed of the host vehicle is below a preselected host threshold.