Adaptive Radar Thresholding for Motion Detection
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Solution Overview
Problem
Current radar systems face challenges in setting an optimal threshold for detecting target motion while minimizing false alarms, especially in environments with disturbances and interferences.
Innovation Solution
The proposed solution involves an apparatus and method that process the magnitude of a frequency spectrum of a radar sensor's receive signal. The frequency spectrum is divided into symmetric portions, and bin thresholds are determined based on the magnitude of opposing bins, allowing for adaptive detection of target motion.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a fixed threshold is used for detecting target motion, then the detection process is simple, but false alarms increase due to disturbances and interferences
Solution Approach 1:
The patent applies dynamics by transforming the static fixed threshold into a dynamic adaptive threshold that automatically adjusts based on the signal environment. The processing circuitry determines thresholds adaptively by analyzing the frequency spectrum and identifying signal portions, allowing the threshold to vary with changing conditions while maintaining reliable detection without excessive complexity.
Solution Approach 2:
The patent changes the threshold parameter from a fixed value to a dynamically determined value based on signal characteristics. By analyzing the frequency spectrum and determining thresholds adaptively according to the magnitude of the frequency spectrum in different portions, the system optimizes detection accuracy while responding to environmental variations.
2Measurement precision
If a low threshold is set to detect minor motions, then detection sensitivity increases, but false alarms from disturbances increase
Solution Approach 1:
The patent segments the frequency spectrum into different portions (first portion and second portion) and applies different thresholding strategies to each. By dividing the spectrum and determining thresholds adaptively for each portion based on the magnitude in corresponding portions, the system can detect minor motions in relevant segments while filtering out disturbances in other segments, thus improving sensitivity without increasing false alarms.
Solution Approach 2:
The patent applies local quality by determining thresholds locally for different portions of the frequency spectrum rather than using a global threshold. The processing circuitry analyzes the magnitude in specific portions and determines thresholds tailored to each portion's characteristics, allowing high sensitivity in regions with target signals while maintaining robustness against disturbances in other regions.
3Reliability
If a high threshold is set to reduce false alarms, then reliability improves, but detection of minor motions is lost
Solution Approach 1:
The patent uses dynamics to make the threshold adaptive rather than fixed. By continuously analyzing the frequency spectrum magnitude and determining thresholds based on the identified signal portions, the system maintains high reliability by adjusting thresholds to match actual signal conditions, enabling detection of minor motions when present while reducing false alarms when absent.
Solution Approach 2:
The patent changes the threshold parameter dynamically based on the analyzed signal characteristics. The processing circuitry determines thresholds adaptively by examining the magnitude of the frequency spectrum in different portions, allowing the threshold to be high when disturbances are present and low when target signals are detected, thus resolving the contradiction between reliability and precision.
4Measurement precision
If adaptive thresholding is implemented to improve detection accuracy, then measurement precision increases, but processing complexity increases
Solution Approach 1:
The patent manages processing complexity by segmenting the frequency spectrum into manageable portions and applying threshold determination to each portion separately. The processing circuitry divides the spectrum, analyzes the magnitude in each portion, and determines thresholds adaptively for each segment, making the complex adaptive process more tractable and efficient.
Solution Approach 2:
The patent implements adaptive thresholding by changing the threshold parameter based on the analyzed frequency spectrum magnitude. The processing circuitry determines thresholds dynamically according to the signal characteristics in different portions, achieving high measurement precision while the parameter change approach keeps the processing methodology systematic and manageable.
Data Source
AI summary
In accordance with an embodiment, a method includes: obtaining a magnitude of a frequency spectrum of a receive signal of the radar sensor, wherein the frequency spectrum comprises a first portion and a second portion within a frequency bandwidth divided into bins, and wherein the first and second portions are symmetrically positioned with respect to a center frequency; for at least one bin in the first portion, determining a bin threshold based on the magnitude of the frequency spectrum within one or more bins in the second portion; for at least one bin in the second portion, determining a bin threshold based on the magnitude of the frequency spectrum within one or more bins in the first portion; and detecting a target motion in response to the magnitude of the frequency spectrum exceeding the bin threshold in at least one bin within the frequency bandwidth.