Moving-Target SAR Phase History Extraction With Doppler Filtering
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Solution Overview
Problem
Conventional SAR systems require computationally expensive image-based processing to convert phase history data into images for detecting moving targets, which can be compromised by motion-induced distortions.
Innovation Solution
Extract phase history directly from SAR data using doppler shift frequency filtering and motion correction techniques to isolate and correct phase history for moving targets, bypassing image conversion.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If image-based processing is used to convert phase history data into images for detecting moving targets, then target detection capability is improved, but computational cost increases significantly
Solution Approach 1:
The patent extracts only the relevant phase history data corresponding to moving targets using Doppler frequency filtering, rather than processing the entire SAR scene. By isolating the Doppler frequency range specific to moving targets and extracting only those phase history components, the system achieves accurate target detection while significantly reducing the computational burden of processing all scene data.
2Shape
If conventional image conversion is applied to moving targets, then target visualization is achieved, but motion-induced distortions compromise image quality
Solution Approach 1:
The patent applies motion correction to the extracted phase history data before performing image reconstruction. By correcting the phase history for motion effects in advance, the resulting images of moving targets are free from motion-induced distortions, maintaining high image quality without requiring post-processing corrections.
3Loss of information
If full scene processing is performed to locate moving targets, then comprehensive scene analysis is achieved, but processing time increases
Solution Approach 1:
The patent segments the SAR phase history data by dividing it into different Doppler frequency ranges, identifying and extracting only the segment corresponding to moving targets. This segmentation allows the system to maintain comprehensive analysis capabilities while focusing computational resources only on the relevant time-frequency segment, thereby reducing overall processing time.
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
Reduces computational burden and minimizes motion-induced distortions, enabling efficient target recognition and image reconstruction for moving objects.
Implementation Method 1
A doppler shift frequency range for the moving target is determined based at least in part on an azimuth angle spread corresponding to the ROI and a known approximate trajectory of the moving target
Data Source
AI summary
A method for synthetic aperture radar (SAR) phase history extraction includes receiving, at a SAR system, a set of SAR phase history data derived from a plurality of return signals, the plurality of return signals produced by the SAR system illuminating a scene with a plurality of radar pulses. A region of interest (ROI) is obtained, the ROI corresponding to a moving target within the scene. A doppler shift frequency range for the moving target is determined based at least in part on an azimuth angle spread corresponding to the ROI and a known approximate trajectory of the moving target. The SAR phase history data is filtered to give extracted phase history corresponding to the moving target based at least in part on the doppler shift frequency range.