Radar Detection Device Using Doppler Fourier Transform for False Alarm Reduction
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Solution Overview
Problem
Existing body proximity sensing technologies face challenges in accurately detecting human bodies due to changes in the surrounding environment and false detections caused by stationary objects.
Innovation Solution
A detection device and method that utilize processing circuitry to perform range Fourier transforms and Doppler Fourier transforms on pulse signals, maintaining and updating reference signals based on the presence or absence of non-zero Doppler values, and using a constant false alarm rate (CFAR) to accurately detect human bodies.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If body proximity sensing is performed using conventional methods, then detection capability is provided, but false detections occur due to changes in surrounding environment and stationary objects
Solution Approach 1:
The system performs preliminary action by maintaining a reference signal from previously received pulse signals before performing detection. This reference signal represents the surrounding environment when no human body is present, allowing the system to pre-establish a baseline for comparison and eliminate false detections from stationary objects
Solution Approach 2:
The system extracts and removes the reference signal component from the current pulse signal through subtraction. By taking out the environmental background (reference signal) from the total signal, the system isolates only the human body signal, eliminating false detections from stationary objects and environmental changes
Solution Approach 3:
The system uses feedback by comparing the current pulse signal with the maintained reference signal. The difference between these signals provides feedback about human body presence, allowing the system to distinguish between environmental changes and actual human body detection
2Measurement precision
If conventional detection methods are used, then general detection is achieved, but ultra-close range detection capability is insufficient
Solution Approach 1:
The system applies parameter changes by performing Fourier transform on the pulse signals to convert them from time domain to frequency domain. This transformation changes the signal representation parameters, enabling the system to detect ultra-close range human bodies by analyzing frequency characteristics that are not visible in the time domain
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
The solution effectively reduces false detections and enables ultra-close range detection of human bodies, improving the accuracy and reliability of body proximity sensing.
Implementation Method 1
perform range Fourier transform on a plurality of pulse signals to obtain first Fourier transform data
Implementation Method 2
perform Doppler Fourier transform on the first Fourier transform data to obtain second Fourier transform data
Data Source
AI summary
A detection device includes processing circuitry configured to perform range Fourier transform on a plurality of pulse signals to obtain first Fourier transform data, perform Doppler Fourier transform on the first Fourier transform data to obtain second Fourier transform data, maintain a reference signal in response to determining the second Fourier transform data includes a non-zero Doppler value, update the reference signal in response to determining the second Fourier transform data does not include any non-zero Doppler values, and determine that a body exists in response to determining a signal magnitude of the plurality of pulse signals is lower than a threshold value, remove the reference signal from the first Fourier transform data in response to determining the signal magnitude is higher than the threshold value to obtain corrected data, and detect that the body exists based on a constant false alarm rate (CFAR) for the corrected data.