Radar Signal Separation for Weak Reflector Phase Analysis
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Solution Overview
Problem
Current image analysis methods struggle to accurately analyze the phase of reflectors with weak reflection and handle nonlinear deformations, especially when strong and weak reflectors are superimposed, due to issues like layover and the limitations of existing phase change models.
Innovation Solution
An image analysis device and method that utilize a phase gradient model to separate signals from radar images, constraining phase differences between nearby pixels to extract components consistent with the model, allowing for the analysis of weakly reflecting reflectors and nonlinear deformations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If SAR images are used to analyze transmission steel towers, then ground surface deformation can be detected, but layover occurs causing mixed reflected waves from the tower and ground surface making phase analysis difficult
Solution Approach 1:
The reflected wave signal is segmented into multiple components corresponding to different reflectors (transmission steel tower and ground surface). The signal separation unit divides the mixed reflected wave into separate signals by comparing with reference signals from each reflector type, enabling independent phase analysis of each component without layover interference
Solution Approach 2:
Reference signals are introduced as intermediaries to facilitate the separation of mixed reflected waves. By comparing the received signal with reference signals from known reflectors (tower and ground surface), the system can identify and separate the contribution of each reflector, acting as a mediator to resolve the layover problem
2Adaptability or versatility
If conventional SAR analysis methods are used, then linear deformation can be estimated, but nonlinear deformation of buildings caused by scour or earthquakes cannot be detected
Solution Approach 1:
The analysis method transitions from static linear deformation models to dynamic nonlinear deformation modeling. By tracking phase changes over time series SAR images and allowing for non-linear phase evolution patterns, the system can detect and analyze nonlinear deformations such as building tilting or collapse caused by scour or earthquakes, rather than assuming only linear displacement
3Measurement precision
If SBAS method is used for time series analysis, then nonlinear deformations can be handled, but only deformation of one specific reflector can be estimated when multiple reflectors are present
Solution Approach 1:
The SBAS deformation analysis is applied separately to each separated reflector signal. After the signal separation unit divides the mixed reflected wave into individual reflector components, the deformation analysis unit can independently perform nonlinear deformation estimation for each reflector using SBAS, preserving both the nonlinear deformation capability and the ability to analyze multiple reflectors simultaneously
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
Enables the analysis of weakly reflecting reflectors and nonlinear deformations even in superimposed states, improving the accuracy of deformation analysis by separating phase components effectively.
Implementation Method 1
a radar mounted on a flying object such as an artificial satellite, an aircraft, or the like transmits and receives a radio wave
Implementation Method 2
the phase difference between radio signals of multiple (for example, two) SAR images taken at different times is calculated
Implementation Method 3
a reflected wave from the transmission steel tower or the high-rise building is mixed with a reflected wave from the ground surface
Data Source
AI summary
The image analysis device includes a signal separation unit 10 which inputs a plurality of radar images in which the same area is captured and a phase gradient model representing a phase difference between a plurality of nearby pixels on a surface of an object to be analyzed that may exist in the radar image, and extracts from the radar image a component consistent with the phase difference represented by the phase gradient model.