Low-Power Radar Signal Detection via Image Processing
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Solution Overview
Problem
Conventional signal processing methods are ineffective for detecting radar signals with low transmission power, leading to low signal-to-noise ratios that render these radars undetectable to interceptors, posing a strategic challenge, especially in military and security contexts.
Innovation Solution
A method involving digitization of radar signals, Fast Fourier Transform (FFT) processing to generate spectra and images, followed by image processing steps such as contour detection, thresholding, dilation, and grouping of contiguous white pixels to enhance signal detection and reduce noise, allowing for the identification of radar signals with low transmission power.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional signal processing methods are used, then high transmission power radar signals can be detected with reasonable accuracy, but low transmission power radar signals cannot be detected due to very low signal-to-noise ratio
Solution Approach 1:
The patent transforms the radar signal detection problem from traditional time-frequency analysis into image processing domain. By converting spectrograms into visual images and applying image processing techniques (edge detection, thresholding, dilation, contour analysis), the system detects low-power radar signals that are indistinguishable from noise in conventional processing. This dimensional transformation enables detection of signals with very low signal-to-noise ratio by exploiting spatial patterns in the image domain.
Solution Approach 2:
The patent replaces conventional signal processing algorithms with image processing algorithms. Instead of using traditional spectral analysis methods, the system converts radar signal spectrograms into images and applies computer vision techniques (edge detection filters, thresholding, morphological operations). This substitution enables effective detection of low-power radar signals by leveraging the pattern recognition capabilities of image processing algorithms.
2Object-affected harmful factors
If low probability interception radar uses low transmission power to remain invisible, then detection difficulty increases, but this creates a strategic advantage for stealth
Solution Approach 1:
The patent converts the harmful effect of low signal-to-noise ratio (which makes LPI radars undetectable) into a beneficial feature. By transforming the detection challenge into an image processing problem, the system exploits the visual patterns that emerge in spectrogram images even when signals are buried in noise. The low-power signals that were previously undetectable now produce detectable spatial patterns in the image domain, allowing the interceptor to detect LPI radars while they maintain their low transmission power advantage.
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 enables the detection and interpretation of low transmission power radar signals, improving sensitivity by up to 20dB and allowing for the differentiation of signal from noise, making these radars detectable and interpretable.
Implementation Method 1
a second step (E2) of generating spectra and at least one image, from the digitized signal obtained in the first step (E1), via an FFT (Fast Fourier Transform) processing
Data Source
Figure 1A~1B
Figure 2A~2B
AI summary
The present invention relates to a method for post-processing low-power radar signals, in particular for LPI (Low Probability of Interception) type radars, said method comprising the main steps of digitizing the analog signal emitted by the radar and recorded by an intercepting device, generating spectra and at least one image from the digitized signal, processing the image obtained, measuring segments of the image from the number of contiguous white pixels along the x-axis, removing segments with low pixel density and converting the detection of the pixelated signal into megahertz and milliseconds, by a frequency deviation along the y-axis and by a time along the x-axis, for reading and interpretation.