Planet Topography Sensor Fusion for Pixel-Level Co-Registration
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Solution Overview
Problem
Current sensor systems face challenges in co-registering optical and microwave datasets due to their distinct technical specifications and operational differences, leading to errors, time consumption, and limited accuracy in pixel-level data fusion.
Innovation Solution
A sensor system with synchronized and aligned optical, infrared, and microwave sensors mounted on a vehicle, utilizing a synchronizer unit to facilitate simultaneous operation and spatially and temporally matched dataset capture, enabling pixel-level co-registration.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If optical sensors are used for data acquisition, then color and infrared properties can be sensed, but data can only be acquired during daytime with clear sky (25% usage)
Solution Approach 1:
The patent combines optical sensors and microwave sensors into a single integrated sensor system mounted on a common platform. This merging allows simultaneous acquisition of both optical data (for color and infrared properties) and microwave data (for geometry and all-weather operation), eliminating the time loss associated with using only optical sensors during limited clear-day conditions.
2Reliability
If microwave sensors are used for data acquisition, then data can be acquired irrespective of time and weather, but sensitivity to geometry is limited
Solution Approach 1:
The integrated sensor system merges microwave sensors with optical sensors, allowing the microwave component to provide reliable all-weather data acquisition while the optical component contributes superior geometric sensitivity. The fusion of data from both sensors achieves measurement precision that compensates for the microwave sensor's limited geometric sensitivity.
3Loss of information
If pixel-level data fusion is performed on datasets from distinct sources, then detailed insights can be achieved, but co-registration errors increase and processing time increases
Solution Approach 1:
By merging optical and microwave sensors into a single integrated system with common mounting and synchronized operation, the patent eliminates co-registration errors that arise from processing datasets from distinct sources. The sensors naturally capture spatially and temporally aligned data, enabling accurate pixel-level fusion while reducing processing time.
Solution Approach 2:
The sensor system performs preliminary synchronization and alignment of optical and microwave data acquisition before fusion processing. The synchronizer unit ensures that both sensors capture data simultaneously and in precise spatial correspondence, preparing the datasets for seamless pixel-level fusion without requiring extensive post-processing correction.
4Loss of information
If pixel-level data fusion is performed on datasets from distinct sources, then detailed insights can be achieved, but processing time and effort increase
Solution Approach 1:
The integrated sensor system merges optical and microwave sensors with synchronized operation, eliminating the need for complex post-acquisition co-registration processes. This merging enables direct pixel-level fusion of already-aligned datasets, dramatically improving data processing efficiency while retaining all detail information.
Solution Approach 2:
The system performs preliminary synchronization of data acquisition during the sensing phase itself, using a synchronizer unit to ensure both sensors capture data simultaneously. This preliminary action eliminates the need for time-consuming post-processing alignment operations, thereby improving productivity.
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
Enhances data accuracy and efficiency by allowing simultaneous data acquisition from multiple sensors, maintaining dataset integrity and enabling detailed insights through pixel-level fusion, overcoming cloud interference and improving data availability.
Implementation Method 1
The optical sensor is a passive sensor, requiring an external source of radiation, like the sunlight, to be able to acquire data. Working in the Visible & Infrared region of the EM Spectrum, they can sense colour of the object being sensed
Implementation Method 2
The second type of sensor used is microwave sensor (Radar Sensor). This is an active sensor, i.e., it sends its own radiation and captures it back. While working in the Microwave region of the EM Spectrum, they can sense the returning waves, which vary based on the geometry of the object being sensed
Data Source
AI summary
A sensor system for sensing topography of a planet is disclosed herein. The system comprises at least one on-board processor. The system further comprises at least one first and second configured on a vehicle moving at a height from a crust portion of the planet for sensing the topography of a sample area of the planet. The sensors are communicatively coupled to the on-board processor. The system comprises a memory communicatively coupled to the on-board processor, wherein the memory stores executable instructions that, when executed by the processor, cause the processor to facilitate synchronized and aligned orientation of the sensors in a direction towards the sample area for sensing spatially and temporally matched datasets. The processor then receives and processes the spatially and temporally matched datasets to achieve pixel level co-registration thereof.