UWB Occupancy Sensing via Channel Impulse Response Classification
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current occupancy sensing technologies in vehicles lack accuracy and efficiency, particularly in providing real-time, per-seat occupancy information for enhanced user experience and regulatory compliance, especially in environments with strong multi-path signals like in-vehicle settings.
Innovation Solution
The implementation of ultra-wideband (UWB) keyless infrastructure using a plurality of UWB transceiver nodes that receive channel impulse response (CIR) measurements, processed by a classification model to predict occupancy based on CIR tensors, leveraging existing keyless entry systems for accurate and energy-efficient occupancy sensing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional occupancy sensing technologies are used, then basic occupancy detection can be achieved, but accuracy and real-time performance are insufficient
Solution Approach 1:
The patent replaces traditional mechanical or simple sensor-based occupancy detection with ultra-wideband electromagnetic wave-based sensing. UWB technology uses electromagnetic waves to measure time of flight and signal characteristics, enabling more accurate and real-time occupancy detection compared to conventional methods. The system processes channel impulse response measurements through classification models to achieve both high accuracy and real-time performance.
2Ease of operation
If occupancy sensing systems are deployed to provide per-seat information, then user experience improves, but system complexity increases
Solution Approach 1:
The patent leverages existing ultra-wideband keyless entry infrastructure to provide multiple functions: occupancy detection, per-seat classification, and real-time monitoring. By reusing the same UWB transceiver nodes already installed for keyless entry, the system avoids adding separate dedicated sensors for each function, thereby reducing overall system complexity while enhancing user experience through comprehensive occupancy awareness.
3Measurement precision
If advanced sensing algorithms are applied to improve occupancy classification, then detection accuracy improves, but computational requirements and energy consumption increase
Solution Approach 1:
The patent performs preliminary signal processing by capturing and storing channel impulse response measurements from UWB transceiver nodes. These pre-processed measurements are then fed into classification models that run on available computational resources. By preparing the data in advance and using efficient classification algorithms, the system achieves high accuracy occupancy classification while managing power consumption through optimized processing approaches.
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 solution provides precise, real-time occupancy detection with low interference and power consumption, suitable for in-vehicle environments, supporting regulatory requirements and enhancing user experience through accurate per-seat occupancy classification.
Implementation Method 1
Channel impulse response (CIR) measurements are received from a plurality of UWB transceiver nodes arranged about a plurality of locations
Data Source
AI summary
Occupancy sensing using ultra-wideband (UWB) keyless infrastructure is provided. Channel impulse response (CIR) measurements are received from a plurality of UWB transceiver nodes arranged about a plurality of locations. A classification model it utilized to predict occupancy of each of the plurality of locations based on CIR tensors formed from the CIR measurements for each of the UWB transceiver nodes.