Radar Image Registration Manager Aligning SAR Imagery with Digital Elevation Models
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Solution Overview
Problem
Current sensor technologies face challenges in aligning and combining images from different sensors, such as synthetic aperture radar and electrical optical sensors, due to issues like layover and occlusion phenomena, which result in misleading information and incomplete views of landscapes.
Innovation Solution
A radar image registration manager system that automatically aligns primary sensor images with digital elevation models, using geospatial coordinates to correct for sensor phenomena and create a holistic view by integrating data from multiple sensors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If multiple sensor types (SAR, LIDAR, electrical optical) are used to image a landscape, then the data set provides different advantages and more comprehensive information, but the images from different sensors cannot be properly aligned and combined due to layover and occlusion phenomena
Solution Approach 1:
The patent uses digital elevation models (DEMs) as an intermediary reference framework to align SAR and electrical optical sensor images. The DEM provides a common geospatial coordinate system that mediates between different sensor types, enabling accurate registration despite layover and occlusion phenomena. The registration manager systematically uses the DEM to transform coordinates and perspectives between different sensor images.
Solution Approach 2:
The patent changes spatial parameters (coordinates, elevation, perspective) to align images from different sensors. By transforming the electrical optical image coordinates to match the SAR image coordinates using DEM-derived geospatial parameters, the system resolves misalignment issues. This involves changing position, orientation, and scale parameters to achieve proper registration.
2Measurement precision
If automatic alignment is implemented to correct layover and occlusion issues, then the accuracy of landscape representation is improved, but the complexity of the registration system increases
Solution Approach 1:
The registration manager performs automatic self-alignment of sensor images using the DEM as reference. The system autonomously calculates transformation parameters and applies corrections without manual intervention. This self-service capability achieves high alignment precision while managing system complexity through automation rather than manual processes.
Solution Approach 2:
The patent uses pre-existing digital elevation models (DEMs) as a preliminary reference framework before performing image registration. By having the DEM prepared in advance with accurate geospatial information, the system simplifies the alignment process and achieves high precision without requiring complex real-time calculations during registration.
3Manufacturing precision
If sensor images are aligned with digital elevation models, then orthorectification and geopositioning are improved, but the processing time and computational resources increase
Solution Approach 1:
The system performs preliminary processing by using pre-computed DEM data and pre-established coordinate transformation relationships. By having the elevation model and registration parameters prepared in advance, the actual image alignment process is accelerated while maintaining high orthorectification quality.
Solution Approach 2:
The patent efficiently changes spatial parameters using mathematical transformation formulas that convert between different coordinate systems. By applying direct parameter transformations rather than iterative optimization, the system achieves high-quality orthorectification with reduced computational time and resources.
Data Source
AI summary
A method, a radar image registration manager, and a set of instructions are disclosed. A primary sensor interface 430 may receive a primary sensor image and a camera model of the primary sensor image. A data storage 420 may store a digital elevation model. A processor 410 may automatically align the primary sensor image with the digital elevation model.