Adaptive Threshold Configuration for UWB Radar Object Detection
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Solution Overview
Problem
Conventional UWB radar systems face challenges in accurately detecting moving objects due to varying signal sizes caused by differences in individuals and environmental factors, which are not effectively correlated with existing probability models.
Innovation Solution
An adaptive threshold configuration method for UWB radar systems, involving a device that extracts maximum signal values, sorts signal magnitudes, selects candidate signal indices based on slope variation, sets weighting factors, and configures position-specific thresholds using a scaling factor to differentiate between moving objects and noise.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If a threshold is configured through experiments or probability model (CFAR), then the detection method is simple and easy to implement, but the detection accuracy deteriorates in various environments because signal size varies between adults and children and due to seasonal clothing changes
Solution Approach 1:
The patent implements dynamic threshold adjustment by continuously monitoring signal characteristics and adapting the threshold based on environmental conditions and signal distributions. Instead of using a fixed threshold from experiments or probability models, the system dynamically configures thresholds to match current detection conditions, thereby maintaining high detection accuracy across varying environments while automatically adapting to different signal characteristics.
Solution Approach 2:
The patent changes the threshold parameter based on observed signal characteristics and environmental conditions. By monitoring signal size variations due to different factors (adult vs. child targets, seasonal clothing changes), the system adjusts the threshold parameter dynamically, transforming a static threshold configuration into an adaptive one that responds to changing detection conditions.
2Device complexity
If a fixed threshold determined by experiments or probability model is used, then the system complexity is low, but the adaptability to various environments deteriorates when signal distribution does not correlate with existing probability models
Solution Approach 1:
The patent enables the detection system to self-adjust and self-optimize by automatically analyzing signal characteristics and configuring appropriate thresholds without external intervention. The system monitors its own detection environment, identifies signal distribution patterns, and autonomously adapts the threshold configuration, thereby achieving high environmental adaptability while maintaining relatively simple system architecture through self-service mechanisms.
Solution Approach 2:
The patent implements feedback loops where detection results and signal characteristics are continuously monitored and fed back to the threshold configuration mechanism. This feedback enables the system to learn from detection outcomes and adjust thresholds accordingly, improving adaptability to various environments while keeping system complexity manageable through iterative self-improvement.
Data Source
AI summary
Disclosed are a method and a device for adaptively configuring a threshold for object detection by means of radar, the device including: a position-specific maximum signal value extraction unit extracting a maximum value of a signal for each position by obtaining the signal when there is no moving object; a position-specific signal magnitude sorting unit obtaining signals caused by a moving object, and sorting magnitudes of the obtained signals for each position in descending order for a time index; a candidate signal index selection unit selecting a candidate signal index; a signal index determination unit setting weighting factors for the respective signals up to the candidate signal index, and determining a sum of the weighting factors as a signal index; and a position-specific threshold configuring unit configuring the threshold for each position by using a signal of the determined signal index and a scaling factor.