Starfield Attitude Estimation via Compressive Sampling
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Solution Overview
Problem
Current star-tracking systems require large amounts of memory and processing power to accurately determine the attitude of an object based on starfield images, which can be costly and power-intensive, especially in radiation-hardened environments.
Innovation Solution
The use of compressive sampling techniques to capture and process starfield image data, allowing for attitude estimation using compressed data, reducing memory and processing requirements while eliminating noise by comparing multiple views of the starfield.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional star-tracking systems acquire and store large numbers of starfield images in memory, then measurement precision is improved, but device complexity and power consumption increase
Solution Approach 1:
The patent extracts only the essential information from starfield images by identifying and recording star positions and intensities rather than storing complete images. This selective extraction of critical data points maintains attitude estimation accuracy while dramatically reducing memory requirements and processing complexity
Solution Approach 2:
The patent applies different processing qualities to different parts of the data: full-resolution processing is applied only to regions containing stars, while non-star regions are discarded. This localized high-quality processing maintains measurement precision for attitude estimation while reducing overall device complexity
2Reliability
If radiation-hardened memory and circuits are used to protect against computational errors, then reliability is improved, but device complexity and cost increase
Solution Approach 1:
The patent reduces the amount of data stored in memory to only essential star position and intensity information, thereby reducing the memory capacity required and the associated radiation-hardening complexity while maintaining sufficient data for reliable attitude estimation
Solution Approach 2:
The patent uses software-based error detection and correction mechanisms that create virtual copies and checksums of critical data in memory, providing radiation error protection through computational redundancy rather than hardware complexity
3Measurement precision
If multiple starfield images are acquired and averaged to reduce noise, then measurement precision is improved, but power consumption and processing time increase
Solution Approach 1:
The patent extracts star position and intensity data from individual images and performs noise reduction by comparing only these extracted features across multiple images, rather than averaging entire images. This selective feature comparison maintains noise reduction effectiveness while significantly reducing processing time and power consumption
Solution Approach 2:
The patent processes only the necessary portion of image data (star locations and intensities) rather than performing full image averaging. This partial processing approach achieves sufficient noise reduction for accurate attitude estimation without the excessive power consumption of complete image processing
Data Source
AI summary
In general, in one embodiment, a starfield image as seen by an object is analyzed. Compressive samples are taken of the starfield image and, in the compressed domain, processed to remove noise. Stars in the starfield image are identified and used to determine an attitude of the object.