Vehicle Radar Velocity Estimation Using Partial Volume Segmentation
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Solution Overview
Problem
Vehicle radar systems face challenges in accurately determining the relative velocity between a host vehicle and objects in its blind spot, particularly when small vehicles are near stationary objects, leading to incorrect detection of moving objects.
Innovation Solution
A vehicle radar system that divides the detection volume into partial volumes and performs velocity estimation along a side extension perpendicular to the forward direction, allowing for more accurate separation of moving objects from background clutter by checking changes in velocity distribution across these volumes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If a cluster of all measurement points is used to calculate average velocity, then the calculation is simple, but the relative velocity becomes inaccurate when small vehicles are near stationary objects
Solution Approach 1:
The detection volume is divided into multiple partial volumes (first, second, third partial volumes) along the side extension direction. Velocity estimation is performed separately for each partial volume, allowing the system to isolate and analyze velocity distributions in different spatial regions. This segmentation enables accurate identification of small moving vehicles by comparing velocity patterns across adjacent partial volumes, rather than mixing all measurements into a single average.
2Area of stationary object
If velocity estimation is performed for the entire detection volume, then coverage is complete, but the ability to distinguish moving objects from background clutter is reduced
Solution Approach 1:
The detection volume is segmented into multiple partial volumes to enable localized velocity analysis. By performing velocity estimation separately for each partial volume and comparing the distributions, the system can identify regions with anomalous velocity patterns that indicate moving vehicles, while maintaining complete coverage of the entire detection area.
Solution Approach 2:
Different regions of the detection volume are analyzed with different approaches. The system performs velocity estimation for each partial volume and compares the distributions to identify local anomalies. This allows the detection algorithm to adapt to local conditions and reliably distinguish moving objects from stationary background clutter in each specific region.
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 provides a more stable and reliable relative velocity difference between the host vehicle and target objects, effectively distinguishing smaller moving vehicles from stationary background objects.
Implementation Method 1
The radar system is arranged to provide range, azimuth angle and radial velocity for a plurality of measurement points at the objects
Data Source
AI summary
A vehicle radar system (3) mounted in a host vehicle (1) arranged to run in a forward running direction (D). The vehicle radar system (3) includes a transceiver arrangement (7) to generate and transmit radar signals (4), and to receive reflected radar signals (5), the transmitted radar signals (4) have been reflected by one or more objects (6, 12). The radar system (3) provides range (rn), azimuth angle (θn) and radial velocity (vm) for a plurality of measurement points (9, 9′) at the objects (6, 12). The radar system (3) is divides a total detection volume (8) into at least two partial volumes (8a, 8b, 8c, 8d), and performs a velocity estimation for each partial volume (8a, 8b, 8c, 8d) such that a total velocity distribution (14) is acquired along a side extension (E) that is perpendicular to an extension along the vehicle forward running direction (D).