Rotating Sparse Array Interferometric Radiometer for Geostationary Imaging
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Solution Overview
Problem
Current space-borne radiometers in low-Earth orbit provide good spatial resolution but poor temporal resolution, while those in geostationary orbit cannot achieve satisfactory spatial resolution due to impractical antenna sizes required, and existing interferometric radiometers face challenges with calibration, sidelobes, and multi-band operation.
Innovation Solution
A sparse array of receiving elements rotated around an axis directed toward the target scene, allowing for optimized sampling of the u-v plane without close-packing, reducing the number of elements needed and enabling high-resolution imaging from geostationary orbit with improved calibration and multi-band capabilities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a large antenna is used in geostationary orbit to achieve high spatial resolution, then spatial resolution is improved, but the antenna size becomes impractical for launch and deployment
Solution Approach 1:
The single large antenna is segmented into multiple smaller receiving elements arranged in a sparse array configuration. These distributed elements work together through interferometric processing to synthesize the aperture of a much larger antenna, achieving high spatial resolution without requiring a single large physical structure that would be impractical to launch and deploy in geostationary orbit
Solution Approach 2:
The solution transitions from a two-dimensional antenna aperture problem to a three-dimensional solution by distributing receiving elements throughout space in a sparse array. The baseline distances between elements in three-dimensional space provide the equivalent aperture synthesis capability of a large single antenna, while avoiding the launch and deployment constraints of a single large structure
2Measurement precision
If receiving elements are close-packed to satisfy Nyquist sampling criterion, then spatial resolution is improved, but the number of elements and system complexity increases significantly
Solution Approach 1:
The sparse array of receiving elements is made rotatable around an axis directed toward the target scene. By rotating the array and accumulating samples at different rotational positions, the system dynamically samples the u-v plane more completely, achieving satisfactory spatial resolution with fewer elements than a static close-packed array would require
Solution Approach 2:
The rotation of the sparse array provides periodic sampling of the spatial frequency domain. By accumulating interferometric samples at multiple discrete rotational positions, the system periodically revisits different baseline orientations, effectively filling in the u-v plane coverage that would otherwise require many more simultaneously active elements
3Device complexity
If a sparse array is used to reduce the number of elements, then device complexity is reduced, but sampling of the u-v plane becomes insufficient
Solution Approach 1:
The sparse array is made rotatable to dynamically change the baseline orientations sampled. By rotating the array structure around the optical axis and accumulating interferometric measurements at multiple rotational positions, the system transforms a sparsely sampling static array into an effectively densely sampling dynamic array, achieving complete u-v plane coverage with fewer elements
4Measurement precision
If LEO satellite orbit is used to achieve good spatial resolution, then spatial resolution is improved, but temporal resolution and continuous coverage deteriorate
Solution Approach 1:
The system changes the orbital parameter from low-Earth orbit (LEO) to geostationary orbit (GEO). This parameter change fundamentally alters the temporal characteristics, enabling continuous coverage and real-time monitoring. The interferometric sparse array technique compensates for the increased distance by synthesizing a large aperture, maintaining spatial resolution while achieving the desired temporal resolution
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
This approach significantly reduces the number of receiving elements required, simplifies calibration, and allows for multi-band imaging with improved spatial resolution and reduced sidelobes, making high-resolution Earth imaging from geostationary orbit feasible while maintaining sensitivity and temporal resolution.
Implementation Method 1
for imaging a radiation emission from a target scene
Implementation Method 2
The complex cross-correlation signal, expressed as a function of the spacing between antennas ('baseline'), is known as 'visibility function' and is essentially the Fourier transform of the brightness of the observed scene
Data Source
AI summary
A space-borne interferometric radiometer for imaging a radiation emission from a target scene (ED), comprising a plurality of receiving elements arranged in a two- or three-dimensional array (REA), a first signal processor (SP1) for computing a two-dimensional set of samples of a visibility function by pair-wise cross-correlating signals received by the receiving elements; and second signal processor (SP2) for reconstructing an image from the samples of the visibility function. The radiometer is further characterized in that it has the ability for rotating the two- or three-dimensional array (REA) about a rotation axis (z) which is substantially directed toward the target scene (ED) and in that the second signal processor (SP2) is adapted for reconstructing the image from a plurality of two-dimensional sets of samples of the visibility function corresponding to different rotational positions of the rotating two- or three-dimensional array (REA) of receiving elements.