Occupant Position Estimation Using Human-Specific Signal Fluctuations
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing technologies struggle to accurately estimate the position of each occupant in a vehicle cabin while distinguishing between occupants, often mistakenly identifying large luggage as human presence due to similar radio signal variations.
Innovation Solution
The proposed solution involves an occupant position estimating device that uses a combination of radars, a transmission control unit, a received strength obtaining unit, a separating unit, a headcount identifying unit, a distance identifying unit, and an occupant position estimating unit to isolate and identify the position of each occupant based on human-specific fluctuations in radio wave reception.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Difficulty of detecting and measuring
If radar-based detection is used to identify occupants, then detection capability is improved, but misidentification of luggage as occupants occurs
Solution Approach 1:
The system dynamically analyzes the temporal characteristics of radio wave reflections by examining waveforms over time. It identifies occupants based on human-specific dynamic patterns such as breathing and body movements, which cause characteristic fluctuations in the reflected radio wave signals. This dynamic analysis allows the system to distinguish between stationary objects like luggage and living occupants, resolving the misidentification problem while maintaining high detection capability.
2Measurement precision
If multiple radars are used to improve position estimation accuracy, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The system employs multiple radars that serve dual functions: both transmitting radio waves for detection and receiving reflected waves for analysis. Each radar unit is multifunctional, performing both transmission and reception tasks, which improves position estimation accuracy through multiple measurement angles while avoiding the need for separate dedicated transmission and reception devices, thereby controlling system complexity.
3Reliability
If waveform separation processing is applied to distinguish occupants, then identification accuracy is improved, but processing complexity increases
Solution Approach 1:
The system applies periodic waveform separation processing that leverages the periodic nature of human physiological signals such as breathing. By analyzing waveforms at regular intervals and identifying periodic patterns characteristic of human respiration, the system can separate and identify individual occupants even in complex multi-occupant scenarios. This periodic analysis approach improves identification accuracy while keeping processing complexity manageable through pattern recognition rather than exhaustive analysis.
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 allows for more accurate estimation of occupant positions in the vehicle cabin, avoiding misidentification of luggage as occupants and enabling precise distinction between multiple occupants.
Implementation Method 1
The radars transmit and receive radio waves in the vehicle cabin
Implementation Method 2
The transmission control unit controls each of radars to transmit radio waves
Data Source
AI summary
An occupant position estimating device includes a transmission control unit, a received strength obtaining unit, a separating unit, a headcount identifying unit, a distance identifying unit, and an occupant position estimating unit. The transmission control unit controls each of radars to transmit radio waves. The received strength obtaining unit obtains multiple received strengths of the radio waves that are received by the respective radars. The separating unit obtains separated waveforms for the occupants from waveforms each of which indicates a time variation of the multiple received strengths. The headcount identifying unit identifies a number of the occupants from the separated waveforms. The distance identifying unit identifies distances from each of the radars to the respective occupants based on a timing at which a human-specific fluctuation appears in the separated waveform. The occupant position estimating unit estimates a position of each of the occupants based on the distances.