Radar Sensor Dynamic Zone Masking for Person Detection
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Solution Overview
Problem
Conventional radar-based systems for detecting persons suffer from fixed detection parameters, leading to inaccurate detection, missed events, or false alarms.
Innovation Solution
An apparatus comprising processing circuitry that obtains radar data, defines a detection zone, modifies the radar data to mask undesired zones outside the detection zone, and uses a trained neural network to determine the number of persons within the detection zone.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If fixed detection parameters are used in radar-based systems, then the system structure is simple, but the detection accuracy deteriorates leading to inaccurate detection, missed events, or false alarms
Solution Approach 1:
The patent applies dynamics by replacing fixed detection parameters with dynamic parameter adjustment. The system automatically adapts detection parameters based on environmental conditions and radar data characteristics, allowing the detection zone and parameters to change in real-time to optimize detection accuracy for different scenarios while maintaining manageable system complexity through automated adaptation
Solution Approach 2:
The patent implements parameter changes by modifying detection parameters dynamically based on environmental context. The system adjusts detection zone boundaries, sensitivity thresholds, and other parameters according to the specific environment and radar signal characteristics, transforming the system from static to adaptive parameter configuration to resolve the contradiction between simplicity and accuracy
2Area of stationary object
If the detection zone is expanded to cover more areas, then the coverage area is improved, but the number of false alarms increases due to interference from undesired zones
Solution Approach 1:
The patent applies segmentation by dividing the detection area into distinct zones - a primary detection zone of interest and undesired zones. The system segments the radar data spatially and processingly, applying different detection criteria and masking techniques to different zones, allowing comprehensive coverage while filtering out false alarms from undesired areas through targeted zone separation
Solution Approach 2:
The patent implements extraction by removing and excluding undesired zones from the detection process. The system identifies and extracts harmful interference regions from the overall detection field, applying masking techniques to eliminate false alarm sources while preserving the primary detection zone's integrity, thus achieving clean detection results from a comprehensive coverage area
3Adaptability or versatility
If dynamic parameter adjustment is implemented, then the adaptability to different environments is improved, but the processing time and computational complexity increase
Solution Approach 1:
The patent applies preliminary action by pre-defining detection zones and parameters for common environmental scenarios before actual detection occurs. The system prepares detection configurations in advance for anticipated environmental conditions, allowing rapid adaptation when new environments are encountered without requiring time-consuming real-time parameter optimization, thus reducing processing delays while maintaining high adaptability
Data Source
AI summary
In accordance with an embodiment, a method includes: obtaining radar data indicating a received radar signal of a radar sensor; obtaining data indicating a detection zone in which persons are to be detected; modifying the radar data for masking an undesired zone outside the detection zone; and determining, using a trained neural network, a number of persons within the detection zone based on the modified radar data