Vehicle Seat Occupant Sensing with Orthogonal Heatmap Calibration
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Solution Overview
Problem
Existing sensing systems in vehicles struggle to accurately determine the position and movement of passengers and objects with low latency and high precision, particularly in dynamic environments like vehicle seats, due to challenges in signal interference and drift.
Innovation Solution
Implementing capacitive-based sensors with orthogonal signaling techniques, such as frequency-division multiplexing (FDM) and code-division multiplexing (CDM), and utilizing algorithms like dynamic baseline, heatmap dynamic range mapping, and touch calibration to enhance sensing accuracy and stability, allowing for real-time detection of occupant movements and object interactions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional sensing systems are used in vehicle seats, then the system structure is simple, but the measurement precision and reliability of occupant position and movement detection deteriorate due to signal interference and drift
Solution Approach 1:
The sensing system is divided into multiple independent sensing elements arranged in a matrix pattern within the seat. Each sensing element independently measures local capacitive changes, and the processor integrates these segmented measurements to create comprehensive heatmaps of occupant position and movement, improving overall measurement precision while maintaining manageable system complexity through modular architecture
Solution Approach 2:
Orthogonal signaling techniques are introduced as an intermediary method to transmit multiple sensing signals through shared conductors without interference. By using orthogonal frequencies or codes, the system can multiplex multiple measurement channels over the same physical infrastructure, enhancing detection accuracy without proportionally increasing system complexity
2Productivity
If multiple signals are transmitted during an integration period, then the productivity and information quality improve, but signal interference and drift increase
Solution Approach 1:
The system transmits sensing signals in periodic integration periods with orthogonal characteristics. Each signal is transmitted at distinct orthogonal frequencies or codes during the integration period, allowing multiple measurements to be taken systematically. The periodic structure enables synchronized reception and processing, maintaining signal stability despite multiple simultaneous transmissions
Solution Approach 2:
The system varies signal parameters (frequency, code) in an orthogonal manner during the integration period to encode multiple measurement channels. By changing these parameters according to orthogonal patterns, the system can distinguish between different signals even when transmitted simultaneously, preventing interference and drift while maintaining high sensing throughput
3Measurement precision
If orthogonal signaling techniques are implemented, then signal interference is reduced and measurement precision improves, but device complexity and processing requirements increase
Solution Approach 1:
The orthogonal signaling system is designed to self-demodulate and self-synchronize at the receiver. The orthogonal properties of the transmitted signals enable automatic separation and identification of individual channels without requiring complex external interference management, reducing processing complexity while maintaining high measurement precision
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
The solution enables precise, low-latency detection of passenger movements and object interactions within vehicles, improving the accuracy of heatmaps and reducing signal drift, thereby enhancing safety and comfort by providing reliable data for downstream applications.
Implementation Method 1
capacitive-based sensors
Implementation Method 2
frequency-division multiplexing (FDM) and code-division multiplexing (CDM)
Data Source
AI summary
A sensing system determines movement and position of passengers and objects within a vehicle. The sensing system comprises a group a group of transmitting antennas operably connected to a car seat, each transmitting antenna adapted to transmit a signal that is orthogonal to each other signal transmitted during an integration period; a plurality of receiving antennas, each one of the plurality of receiving antennas adapted to receive transmitted signals; and a processor adapted to determine a measurement of the transmitted signals received and create a heatmap, wherein a heatmap summation is taken during no-touch events, compared to a baseline heatmap, and a new baseline heatmap recalibrated if a threshold is exceeded.