In-Cabin Radar Passenger Counting Under Vehicle Motion Noise
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Solution Overview
Problem
Existing radar sensor systems face challenges in accurately determining the number of passengers in a vehicle passenger compartment, especially in noisy environments caused by vehicle movement, wind, or engine vibrations, leading to detection errors.
Innovation Solution
A radar sensor system method involving a radar transmitting unit, a radar receiving unit, and an evaluation and control unit that performs discrete wavelet transform and Hilbert transform on received radar signals to extract characteristic parameters, which are then used by a trained classifier to identify the number of passengers present, effectively distinguishing between noise and human vital signs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If radar sensor signals are used to detect passenger presence, then contact-free detection is achieved, but detection accuracy deteriorates in noisy environments caused by vehicle movement, wind, or engine vibrations
Solution Approach 1:
The radar sensor signals are divided into multiple frequency components through Fourier transformation. Each frequency component is processed separately to identify and isolate the characteristic frequencies of human vital signs from the noise spectrum, thereby improving detection accuracy in noisy environments
Solution Approach 2:
A classification model trained with supervised learning acts as an intermediary between the raw radar signals and the final detection result. This model learns to distinguish between noise patterns and genuine vital sign patterns, filtering out harmful noise while preserving accurate passenger presence detection
2Measurement precision
If simple radar signal analysis is used, then system complexity is reduced, but the ability to distinguish between noise and human vital signs deteriorates
Solution Approach 1:
The classification model is pre-trained with supervised learning using labeled training data that includes both noise and vital sign patterns. This preliminary training enables the system to automatically distinguish between noise and genuine signals during operation without requiring complex real-time analysis algorithms
Solution Approach 2:
The system transforms the radar signals from time domain to frequency domain through Fourier transformation, changing the parameter representation. This transformation reveals characteristic frequency patterns of vital signs that are not apparent in the raw signal, improving detection precision while maintaining manageable processing complexity
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 method enables accurate detection and classification of the number of passengers, even in non-stationary conditions with high noise levels, by distributing energy from living sources to specific wavelet levels and using supervised learning to achieve high accuracy in passenger counting.
Implementation Method 1
a radar transmitting unit (12) having at least one radar transmitting antenna and being configured for transmitting radar waves towards the vehicle passenger compartment, a radar receiving unit (16) having at least one radar receiving antenna and being configured for receiving radar waves that have been transmitted by the radar transmitting unit and that have been reflected by a passenger or passengers
Implementation Method 2
receiving radar waves that have been transmitted by the radar transmitting unit and that have been reflected by a passenger or passengers
Implementation Method 3
an evaluation and control unit (22) that is at least configured for evaluating Doppler information from the radar waves received by the radar receiving unit
Data Source
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AI summary
A method of operating a radar sensor system (10) for determining a number of passengers (24) in a vehicle passenger compartment (30). The radar sensor system (10) includes at least one radar transmitting antenna (12) and at least one radar receiving antenna (16) and an evaluation and control unit (22) for evaluating Doppler information from the received radar waves (18). The method comprises transmitting radar waves (14) towards the vehicle passenger compartment (30); receiving radar waves (18) reflected by a passenger (24) or by passengers being present in the vehicle passenger compartment (30); generating received radar signals (32) from the received radar waves (18); mathematically decomposing (42) the received radar signals (32) into a plurality of received signal components; providing (44) values of the received signal components regarding a characteristic parameter to a classifier trained with a plurality of scenarios; identifying (46) one of trained scenarios, based on the provided values; and generating (48) an output signal indicative of the identified scenario.