UWB Seat Occupancy Identification Using CIR and Angle-of-Arrival
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Solution Overview
Problem
Current seat occupancy sensors in vehicles are prone to incorrect identification due to weight forces from objects or animals, are costly, and lack resolution in age classification, especially for children.
Innovation Solution
An ultra-wideband (UWB) radar system with a transmitter and receivers, combined with a computer processing channel impulse responses using machine learning algorithms, performs angle-of-arrival calculations to accurately determine seat occupancy, age, and health status, eliminating the need for separate sensors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If seat occupancy sensors with pressure sensors are used to identify seat occupancy, then the occupancy status can be determined from switching states, but incorrect identification occurs due to weight force from objects or animals
Solution Approach 1:
The patent divides the detection task into multiple independent sensing zones within the seat cushion, each with its own switching element. By analyzing the spatial distribution and pattern of activated zones rather than just the total count, the system can distinguish between human occupancy patterns and those caused by objects or animals, thereby improving reliability while reducing false positives.
Solution Approach 2:
The patent introduces an advanced evaluation unit that acts as an intermediary between the pressure sensors and the occupancy determination. This evaluation unit applies machine learning algorithms and pattern recognition to interpret sensor data, serving as a smart mediator that filters out false signals from objects or animals while correctly identifying human occupancy, thus resolving the contradiction between reliability and false positives.
2Reliability
If seat occupancy sensors are installed for each vehicle seat, then occupancy status can be monitored, but the cost increases significantly
Solution Approach 1:
The patent designs a universal seat occupancy sensor system where a single sensor module can be adapted for use in different seat positions and configurations. The evaluation unit processes data from multiple sensors in various patterns, allowing the same hardware platform to serve multiple functions and seat types, thereby reducing overall manufacturing costs while maintaining reliable occupancy monitoring across all seats.
Solution Approach 2:
The patent uses a standardized sensor module design that can be replicated across different seat positions. Rather than designing unique sensor systems for each seat, the same modular sensor unit is copied and deployed throughout the vehicle, significantly reducing development and manufacturing costs while ensuring consistent occupancy monitoring performance across all seats.
3Measurement precision
If traditional seat occupancy sensors are used, then basic occupancy detection is achieved, but resolution for age classification of children is insufficient
Solution Approach 1:
The patent transitions from one-dimensional weight-based detection to multi-dimensional analysis by incorporating spatial distribution of pressure, temporal patterns of weight application, and regional activation patterns across multiple sensing zones. This dimensional expansion enables the system to infer age classification and child presence with high precision without requiring complex additional hardware, as the existing sensor network is analyzed through sophisticated evaluation algorithms.
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 precise and cost-effective seat occupancy identification, controlling vehicle functions such as safety belts and airbags, while providing age and health status classification, enhancing safety and comfort.
Implementation Method 1
the at least two receivers TRx, Rx are configured to receive the preamble symbols reflected by the vehicle seats
Data Source
AI summary
The present invention comprises a device and a method for exact seat occupancy identification in a vehicle. The device comprises an ultra-wideband (UWB) radar comprising a transmitter (TRx) and at least two receivers (TRx, Rx). The transmitter (TRx) is configured to emit a plurality of preamble symbols in the direction of a vehicle seat of the vehicle. The at least two receivers (TRx, Rx) are configured to receive the preamble symbols reflected by the vehicle seats. A computer is configured to generate Channel Impulse Responses (CIRs) from the received, reflected preamble symbols and process the generated CIRs with the aid of a suitable machine learning algorithm. The computer is further configured to perform an angle-of-arrival calculation based on the reflected preamble symbols and determine an occupancy of the vehicle seats from the processed CIRs and the performed angle-of-arrival calculation.