MIMO Radar Occupant Classification via 3D Voxel Imaging
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Solution Overview
Problem
Current MIMO radar imaging techniques struggle to achieve adequate resolvability when identifying targets in close proximity or in moving environments, particularly in vehicle occupancy classification, leading to inefficiencies and increased costs due to the need for multiple sensors.
Innovation Solution
The method employs a MIMO radar system with an array of transmitting and receiving elements to generate 3D complex images, cluster voxels, and analyze their geometrical distribution within the vehicle to classify occupants, using algorithms like DBSCAN and Gaussian distributions for accurate seat occupancy determination.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If MIMO radar imaging techniques are used to identify targets in close proximity, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent combines multiple radar functions (imaging, occupancy detection, classification) into a single MIMO radar system, eliminating the need for separate sensor arrays while maintaining measurement precision for targets in close proximity
Solution Approach 2:
The MIMO radar system performs multiple functions including 3D imaging, occupancy detection, and occupant classification simultaneously, reducing overall device complexity while improving target resolvability through advanced signal processing
2Measurement precision
If multiple sensors are deployed to monitor vehicle occupancy, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent merges occupancy detection, seatbelt status monitoring, and airbag control functions into a single radar-based system, replacing multiple separate sensors while maintaining or improving detection accuracy
Solution Approach 2:
The radar system acts as an intermediary that provides comprehensive occupancy information to multiple vehicle systems (airbag control, seatbelt reminders, occupancy-based features), eliminating the need for separate sensors in each system
3Measurement precision
If advanced MIMO imaging techniques are used in moving environments, then measurement precision is improved, but reliability decreases
Solution Approach 1:
The patent implements dynamic tracking algorithms that adapt to vehicle motion and environmental changes, maintaining measurement precision and system reliability by continuously adjusting to moving conditions rather than relying on static imaging assumptions
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 resolvability and reduces the complexity of the system by accurately classifying occupants and monitoring physiological data, such as breathing and heart rates, without the need for extensive sensor arrays, thereby improving vehicle occupancy monitoring efficiency and reducing costs.
Implementation Method 1
Wideband MIMO radar apparatus based on compact antenna arrays is currently used in various imaging applications to visualize near-field as well as far-field objects and characterize them based on their reflective properties
Implementation Method 2
transmitting a plurality of transmitted radar signals towards a target object set; receiving reflected radar signals
Data Source
AI summary
Using transmitters and receivers for detecting occupants in a vehicle, and classifying those occupants according to the geometry of the vehicle, where sets of complex values associated with voxels in a predetermined region of the vehicle are converted into 3D complex images, where clusters of voxels in the 3D complex images are analyzed to determine presence of occupants, and where positions of seats may determine which seats in the vehicle are occupied.