Vehicle Seat Occupancy Radar with High-Resolution Angle Detection
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing radar-based occupancy detection systems in vehicles suffer from poor angular resolution when multiple occupants are close together and misclassification due to static objects under vibration, especially using MIMO systems with standard signal processing methods like FFT.
Innovation Solution
A method utilizing a frequency-modulated continuous-wave radar signal with a plurality of receive antennas, employing frequency estimation techniques such as Capon or MUSIC algorithms to improve angular resolution, and incorporating range gating and static background removal to distinguish between occupants and static objects.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If standard signal processing methods like FFT are used in MIMO radar systems, then the system complexity is kept manageable, but the angular resolution remains poor and cannot adequately separate closely positioned targets
Solution Approach 1:
The patent changes the signal processing parameter from standard FFT to advanced frequency estimation methods (MUSIC, Capon, ESPRIT) to achieve superior angular resolution. This parameter change in the signal processing algorithm enables the system to resolve closely spaced targets that FFT cannot separate, directly addressing the angular resolution limitation while accepting increased computational complexity.
2Reliability
If radar systems differentiate between humans and inanimate objects using occupant movements, then detection accuracy improves, but static objects under vibration lead to misclassifications
Solution Approach 1:
The patent applies preliminary action by performing static background removal before occupancy detection. The system captures a background signal when the seat is empty and subtracts it from subsequent signals, thereby eliminating vibrations from static objects before they can cause misclassification. This preliminary processing step prevents vibration-induced false detections while preserving genuine occupant signals.
3Measurement precision
If a single radar system surveys multiple seats, then system cost is reduced, but angular resolution deteriorates making it difficult to distinguish occupation of different seats
Solution Approach 1:
The patent changes the signal processing parameters using advanced frequency estimation methods that extract precise angular information from the received signals. By utilizing MUSIC, Capon, or ESPRIT algorithms, the system achieves sufficient angular resolution to distinguish between multiple seats using a single radar system, eliminating the need for multiple radar units while maintaining seat position discrimination capability.
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
Enhances the ability to accurately differentiate between vehicle occupants and inanimate objects, even when they are closely positioned, by significantly improving angular resolution and reducing false classifications.
Implementation Method 1
a radar sensor which is mounted at the ceiling of the car
Implementation Method 2
radar sensors which measure Doppler frequency shifts can provide information on the movement of the target
Implementation Method 3
The phase difference between two channels corresponds to an angle of arrival
Data Source
AI summary
A method for occupancy detection for at least one vehicle seat, using at least one transmit antenna and a plurality of receive antennas, includes: emitting a detection signal with each transmit antenna onto at least one vehicle seat, which detection signal is a frequency-modulated continuous-wave radar signal, and receiving with each receive antenna a reflected signal; recording sample data representing the reflected signal, the sample data having M channels, with M=N1·N2, where N1 is the number of transmit antennas and N2 is the number of receive antennas; for each channel, removing a component from the sample data that corresponds to a reflection from a static object; and applying a frequency estimation method to the sample data to at least implicitly determine at least one angle of arrival θi corresponding to a position of an occupant on a vehicle seat.