Radar Breathing Target Detection via AC DC Signal Separation
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Solution Overview
Problem
Conventional Doppler radars are unable to detect stationary targets, such as a human not in motion, which limits their effectiveness in scenarios like searching for disaster victims or detecting individuals hiding behind obstructions.
Innovation Solution
A computer-implemented method that separates the electric signal from Doppler processors into AC and DC magnitudes, generates AC and DC lines by summing these magnitudes across Doppler cells, and uses a CFAR detector to compare energy spikes in these lines against a threshold to detect stationary breathing targets.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional Doppler radar is used to detect moving objects, then velocity data can be obtained, but stationary targets cannot be detected
Solution Approach 1:
The Doppler spectrum is segmented into multiple frequency bins, with specific focus on low-frequency components (0.1-4 Hz) that correspond to breathing rates. This segmentation allows the system to isolate and analyze breathing-related Doppler shifts separately from other motion components, enabling detection of stationary breathing targets while maintaining capability to detect moving targets
Solution Approach 2:
The system transitions from traditional velocity-based detection to a multi-dimensional approach that incorporates temporal analysis of low-frequency Doppler components. By analyzing the temporal characteristics of signal variations in the 0.1-4 Hz range across multiple pulses, the system adds a time-frequency dimension to detection, enabling distinction between stationary breathing targets and other stationary objects
2Measurement precision
If signal processing complexity is increased to detect stationary targets, then detection accuracy improves, but processing time and computational load increase
Solution Approach 1:
The system performs preliminary filtering of Doppler spectrum components to isolate the 0.1-4 Hz breathing frequency range before detailed analysis. By pre-identifying and extracting only the relevant low-frequency components that correspond to human breathing, the system reduces the amount of data requiring intensive processing while maintaining high detection accuracy for breathing targets
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
This approach allows for the detection of stationary breathing targets, distinguishing them from non-breathing stationary objects, thereby enhancing the radar system's capability to locate and identify individuals in various circumstances.
Implementation Method 1
Conventional Doppler radars use the Doppler effect to produce velocity data about objects at a distance. As indicated in the term 'radar ', that is, radio detection and ranging, a conventional radar system transmits certain bursts of radio frequency energy and detects objects based on echoes of the radio frequency bouncing off the objects within a range of the conventional radar system. The conventional Doppler radars produces the velocity data of the objects by analyzing how an object's motion has altered the frequency of the returned signal.
Data Source
AI summary
A method for radar signal processing separates an electric signal generated by Doppler processors of a radar into alternating current (AC) magnitudes with Doppler frequencies corresponding to absolute values between 0.1 and 4 Hz and direct current (DC) magnitudes with no Doppler frequency. An AC line and a DC line are generated, based on the AC magnitudes and the DC magnitudes, respectively, by adding respective energies across Doppler cells for each range cell and subsequently applying CFAR detector algorithm respectively. An energy level difference between an energy spike in the AC line and another energy spike in the DC line is calculated and compared with a threshold set for detecting a breathing target that is stationary. If the energy level difference is greater than the threshold, the breathing target that is stationary is detected and reported to the radar operator.