Radar Signal Processing for Radio Wave Source Extraction
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Solution Overview
Problem
Existing radar observation methods struggle to distinguish actual radio wave sources from noise when the signal-to-noise ratio is low, as they cannot effectively extract and display radio wave source information.
Innovation Solution
An observation apparatus and method that perform a Fourier transform on received electric field signals, divide signals by antenna pattern spectral functions, and use Prony's method with exponential functions including real and imaginary parts to identify and extract actual radio wave sources by setting thresholds on the real parts of extracted exponential function components.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If Prony's method is used to extract radio wave source information, then radio wave source information can be directly extracted, but noise influence causes false information to be extracted when signal-to-noise ratio is low
Solution Approach 1:
The patent segments the extraction process into two distinct stages: first extracting exponential function components using Prony's method, then separately evaluating their real parts to filter noise. This segmentation allows independent optimization of each stage - extraction sensitivity in the first stage and noise rejection in the second stage.
Solution Approach 2:
Instead of trying to improve the overall extraction process to simultaneously achieve both accuracy and reliability, the patent inverts the approach by using the real part values as a filtering criterion after extraction. This reverse filtering approach maintains extraction accuracy while adding a reliability layer.
2Measurement precision
If deconvolution method is used to improve resolution, then distribution function can be obtained, but radio wave source information cannot be directly extracted
Solution Approach 1:
The patent merges the advantages of both deconvolution method (resolution improvement) and Prony's method (direct information extraction). It uses deconvolution to enhance the distribution function first, then applies Prony's method to the enhanced data, combining the benefits of both approaches.
Solution Approach 2:
The patent performs preliminary deconvolution processing on the distribution function before applying Prony's method. This preliminary action enhances the quality of input data for Prony's method, improving both resolution and subsequent extraction accuracy.
Data Source
AI summary
A signal processing unit performs, on the basis of a received electric field signal from an antenna by which a beam is scanned within a predetermined azimuthal angle and a signal of an azimuthal angle of the scanned beam, a Fourier transform on a distribution function of the received electric field signal into a frequency domain of the azimuthal angle, divides a signal according to a first spectral function by a signal according to a second spectral function, the first spectral function being obtained by performing the Fourier transform, the second spectral function being obtained by performing a Fourier transform on an antenna pattern of the antenna into a frequency domain of the azimuthal angle, and subjects the divided signal to fitting by using Prony's method with exponential functions including real parts and imaginary parts in arguments.