Flash LIDAR Super-Resolution for Spacecraft Landing DEM
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Solution Overview
Problem
Current LIDAR technologies, specifically flash LIDAR, face limitations in generating a Digital Elevation Map (DEM) with sufficient spatial resolution, precision, and size for safe and precise spacecraft landings, as a single frame or mosaic of LIDAR data is insufficient to meet system requirements, particularly during the brief time window of a landing.
Innovation Solution
A super-resolution algorithm is applied to flash LIDAR range data to enhance image processing, allowing for the creation of a DEM with improved accuracy and precision, utilizing sub-pixel shifts between multiple low-resolution images to generate a high-resolution DEM, which is then used for detecting hazardous terrain features and identifying safe landing sites.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a single frame of flash LIDAR data is used to generate DEM, then the processing time is short and real-time capability is maintained, but the spatial resolution and precision are insufficient
Solution Approach 1:
The patent applies preliminary action by pre-aligning and pre-processing multiple LIDAR frames before generating the DEM. The system performs preliminary registration of successive frames based on vehicle position and orientation data, and pre-computes the merged DEM structure, enabling high-resolution output within real-time constraints.
Solution Approach 2:
The patent merges multiple successive frames of flash LIDAR data into a single high-resolution DEM. By combining information from multiple low-resolution frames captured at different time instances, the system achieves enhanced spatial resolution and precision that cannot be obtained from a single frame alone.
2Measurement precision
If multiple frames of flash LIDAR data are processed to improve DEM resolution, then measurement precision improves, but processing complexity and time requirements increase
Solution Approach 1:
The patent segments the DEM generation process into distinct modular steps: frame alignment using vehicle navigation data, projection of LIDAR ranges onto the DEM grid, interpolation of elevation values, and merging of multiple frames. This segmentation reduces processing complexity by making each step independent and computationally efficient.
Solution Approach 2:
The patent processes only the necessary portions of multiple frames that contribute to the final DEM resolution. By selectively processing successive frames and using partial overlap information, the system achieves sufficient precision without the excessive computational burden of processing every possible frame in detail.
3Manufacturing precision
If multiple frames are merged to create high-resolution DEM, then DEM precision improves, but the system requirements and computational resources increase
Solution Approach 1:
The system uses self-service by leveraging vehicle navigation data (position and orientation) that is already being collected for other purposes. This pre-existing navigation information is directly utilized for frame alignment and DEM generation, eliminating the need for separate, resource-intensive alignment processes and improving overall system efficiency.
Solution Approach 2:
The patent changes parameters by dynamically adjusting the number of frames processed, the resolution level of the output DEM, and the temporal window of data used based on real-time mission requirements. This flexibility allows the system to maintain high precision while adapting computational resources to match actual productivity needs.
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
The super-resolution algorithm significantly improves the accuracy and precision of DEM generation, enabling safe and precise spacecraft landings by effectively processing flash LIDAR data in real-time, even under varying trajectory profiles and look angles, and can be used for guidance, navigation, and control of vehicles.
Implementation Method 1
Light reflected from the surface is captured by an array of detectors
Implementation Method 2
an apparatus relying on Light Detection and Ranging ('LIDAR') technology
Data Source
AI summary
A method for creating a digital elevation map (“DEM”) from frames of flash LIDAR data includes generating a first distance Ri from a first detector i to a first point on a surface Si. After defining a map with a mesh Θ having cells k, a first array S(k), a second array M(k), and a third array D(k) are initialized. The first array corresponds to the surface, the second array corresponds to the elevation map, and the third array D(k) receives an output for the DEM. The surface is projected onto the mesh Θ, so that a second distance Rk from a second point on the mesh Θ to the detector can be found. From this, a height may be calculated, which permits the generation of a digital elevation map. Also, using sequential frames of flash LIDAR data, vehicle control is possible using an offset between successive frames.