Automotive Radar Clutter Estimation for Lane Occupancy Detection
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Solution Overview
Problem
Current radar systems struggle to accurately estimate the position and size of clutter beyond their resolution limits, which hinders the provision of reliable lane occupancy information to drivers, especially in scenarios requiring precise control like automatic lane changes and emergency steering.
Innovation Solution
A radar control device and method that includes a receiver for detecting objects, a detector using DBSCAN and FFT to identify clutter, and a determiner estimating clutter position and size in subsequent periods based on relative speed, determining lane occupancy and validity to enhance driver assistance systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Length of stationary object
If radar resolution limits are used for detection, then detection range is extended, but measurement precision of clutter position and size deteriorates
Solution Approach 1:
The system performs preliminary detection of clutter at distant locations beyond radar resolution limits, then uses relative speed information to predict and refine clutter position and size estimates before making final determination. This preliminary action allows extending detection range while maintaining acceptable measurement precision through subsequent refinement steps.
Solution Approach 2:
The system introduces relative speed as an intermediary parameter to bridge the gap between extended detection range and measurement precision. By using relative speed to estimate clutter motion and predict future positions, the system can determine occupancy states of distant lanes more accurately than direct radar detection alone would allow.
2Loss of time
If clutter detection beyond radar resolution is performed, then lane occupancy information is provided more quickly, but reliability of the information deteriorates
Solution Approach 1:
The system uses feedback from relative speed measurements to continuously refine clutter position and size estimates. By comparing detected clutter with estimated clutter based on relative speed, the system can validate its predictions and provide reliability information to the driver, balancing quick information provision with maintained reliability.
Solution Approach 2:
The system performs preliminary estimation of clutter characteristics using relative speed before final occupancy determination. This allows the system to prepare and validate occupancy information in advance, providing it more quickly to the driver while maintaining reliability through the preliminary validation step.
3Measurement precision
If target separation beyond radar resolution is attempted, then lane occupancy determination accuracy is improved, but device complexity increases
Solution Approach 1:
The system uses relative speed as an intermediary to simplify the target separation process beyond radar resolution. Instead of directly separating overlapping targets, the system estimates clutter motion through relative speed and uses this to predict and separate clutter from legitimate targets, reducing processing complexity while improving occupancy determination accuracy.
Solution Approach 2:
The system replaces complex mechanical or computational target separation methods with a more efficient approach using relative speed estimation. By substituting direct spatial separation with motion-based prediction, the system achieves better lane occupancy accuracy with reduced processing complexity.
Data Source
AI summary
The embodiments relate to a radar control device and method. Specifically, a radar control device according to the embodiments may include a receiver configured to receive reception information for detecting objects around a host vehicle at predetermined periods, a detector configured to detect a clutter based on the reception information, and a determiner configured to estimate an estimated clutter in a second period based on a relative speed between a first clutter detected in a first period and the host vehicle, and determine an occupancy state of a lane around the host vehicle based on the estimated clutter.