Stripmap SAR Registration via Range Profile Transformation
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Solution Overview
Problem
Traditional SAR imagery navigation systems face challenges in GPS-denied environments due to high computational complexity and resource requirements, particularly in low SWaP autonomous systems, where noise in SAR images reduces the reliability of feature detection and adds expensive computations.
Innovation Solution
A stripmap synthetic aperture radar system that transforms received stripmap range profile data into partial circular range profile data, comparing it to a template to estimate registration parameters, thereby reducing the need for image reconstruction and feature detection, and utilizing a computationally less intensive processing method.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional image processing techniques are used for SAR image matching and registration, then feature detection and geometric transformation can be performed, but computational complexity and required processing resources increase significantly
Solution Approach 1:
The patent extracts and processes only the essential range profile information from SAR images, discarding redundant image data. By working directly with range profiles rather than full SAR images, the system achieves registration without requiring computationally intensive image reconstruction and feature detection processes.
Solution Approach 2:
The patent transforms the registration problem from the image domain to the range profile domain. This dimensional change allows registration to be performed on simplified one-dimensional range profiles instead of two-dimensional SAR images, significantly reducing computational complexity while maintaining registration accuracy.
2Object-affected harmful factors
If noise mitigation methods are applied to reduce SAR image noise, then noise effects are reduced, but feature detection reliability decreases and computational resources increase
Solution Approach 1:
The patent extracts registration information directly from range profiles before noise mitigation processing is applied. By performing registration on the raw range profile data, the system avoids the need for noise mitigation that would soften and wash out features, while still achieving reliable registration through the inherent structure of range profile data.
3Measurement precision
If extensive SAR image reconstruction and feature detection processing is performed, then registration accuracy can be achieved, but processing time and computational resources increase
Solution Approach 1:
The patent performs preliminary processing by converting SAR images to range profiles and extracting essential registration information before the actual registration computation. This preliminary action simplifies the subsequent registration process, reducing both computational time and resources while maintaining accuracy.
Solution Approach 2:
The patent segments the registration process into distinct stages: range profile extraction, template matching, and parameter estimation. By breaking down the complex registration task into these segmented steps working with simplified range profile data, the system achieves accurate registration with reduced processing time and computational resources.
Data Source
AI summary
Described is a stripmap SAR system on a vehicle comprising an antenna that is fixed and directed outward from the side of the vehicle, a SAR sensor, a storage, and a computing device. The computing device comprises a memory, one or more processing units, and a machine-readable medium on the memory. The machine-readable medium stores instructions that, when executed by the one or more processing units, cause the stripmap SAR system to perform various operations. The operations comprise: receiving stripmap range profile data associated with observed views of a scene; transforming the received stripmap range profile data into partial circular range profile data; comparing the partial circular range profile data to a template range profile data of the scene; and estimating registration parameters associated with the partial circular range profile data relative to the template range profile data to determine a deviation from the template range profile data.