Radar Target Detection Using World Coordinates for ROI Mapping
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Solution Overview
Problem
Defining a region of interest in a radar reference system is challenging due to the difficulty in translating user-defined real-world shapes into the radar's coordinate system, which often does not align with basic spherical or Cartesian volumes.
Innovation Solution
A method using two reference systems, a radar reference system and a world reference system, where the user defines boundaries in the real-world Cartesian system, and a calibration object is used to transfer target positions from radar to world coordinates, allowing for easier and more accurate definition of the region of interest.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If the region of interest is defined in the radar reference system using spherical coordinates, then the radar sensor can directly compare target positions with stored parameters, but the user finds it difficult to set appropriate geometric parameters because the radar reference system does not align with the user's perception of the real world
Solution Approach 1:
The patent introduces a world reference system as an intermediary between the user's intuitive real-world perception and the radar's spherical coordinate system. This intermediary layer allows users to define regions using familiar Cartesian coordinates aligned with the environment, while the system automatically handles the transformation to radar coordinates for detection purposes.
Solution Approach 2:
The patent transitions from the radar's spherical coordinate system (range, azimuth, elevation) to a world reference system using Cartesian coordinates (x, y, z) that align with the physical environment. This dimensional change enables users to think and define regions in terms of familiar spatial relationships rather than abstract angular measurements.
2Productivity
If the region of interest is defined as a basic volume element in spherical coordinates, then the radar sensor can easily determine if a target is inside or outside the region, but the region shape does not well fit the actual physical bodies in the environment
Solution Approach 1:
By transforming from spherical to Cartesian coordinates, the system enables definition of region boundaries that conform to actual physical object shapes in the environment, rather than being constrained to spherical segments. This allows flexible adaptation to various geometries while maintaining efficient detection through coordinate transformation.
3Ease of operation
If the user defines the region of interest based on real-world objects, then the region boundaries are intuitive and easy to set, but the user may not precisely know which coordinates should locate the region in the radar reference system
Solution Approach 1:
The world reference system serves as an intermediary that bridges the user's intuitive understanding of object positions in the real world with the precise radar coordinate system. Users define regions using familiar spatial relationships, and the system automatically performs the coordinate transformation with precise mathematical relationships, eliminating the need for users to manually calculate radar coordinates.
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
Enables users to easily set region boundaries relative to the real world, simplifying the process and improving accuracy by using a one-time calibration with a calibration object, such as a chessboard, and algorithms like OpenCV for image recognition.
Implementation Method 1
the target position is detected in terms of range, that is the distance from the radar determined based on time of flight
Implementation Method 2
Radar sensors are known, for checking the presence of moving or still targets in regions of interest of an environment
Implementation Method 3
An image of the environment is captured by a camera fixed to the radar sensor
Data Source
AI summary
A method of radar detection of targets in a region of interest, comprises storing boundaries of the region of interest, represented in a world reference system of coordinates. A camera fixed to the radar sensor captures an image of the environment, where a calibration object like a chessboard is identified, and based on its position in the captured image, the position and orientation of the radar sensor are determined in the world reference system. The environment is scanned, to determine target positions in a radar reference system of coordinates, centered in the radar sensor. Based on this, the target positions are transferred from the radar reference system to the world reference system, and are compared with the stored boundaries of the region of interest.