A Lightweight Compact Multi-Spectral Imager Using Novel Computer-Generated Micro-Optics and Spectral-Extraction Algorithms

Metadata Updated: November 12, 2020

The objective of this NASA Early-stage research proposal is to demonstrate an ultra-compact, lightweight broadband hyper- and multi-spectral imaging system that is capable of (1) detecting near-Earth objects (NEOs), (2) determining the size of NEOs, (3) determining the rotational characteristics of NEOs and (4) characterizing the material composition and thereby, determining the mass of NEOs. We achieve these goals by utilizing a novel broadband diffractive-optic to disperse incident light, collecting the dispersed image, and then by using new algorithms to reconstruct the incident unknown spectrum.

Access & Use Information

Public: This dataset is intended for public access and use. License: No license information was provided. If this work was prepared by an officer or employee of the United States government as part of that person's official duties it is considered a U.S. Government Work.

Downloads & Resources

Dates

Metadata Created Date November 12, 2020
Metadata Updated Date November 12, 2020

Metadata Source

Harvested from NASA Data.json

Additional Metadata

Resource Type Dataset
Metadata Created Date November 12, 2020
Metadata Updated Date November 12, 2020
Publisher Space Technology Mission Directorate
Unique Identifier Unknown
Maintainer
Identifier TECHPORT_91437
Data First Published 2018-11-01
Data Last Modified 2020-01-29
Public Access Level public
Bureau Code 026:00
Metadata Context https://project-open-data.cio.gov/v1.1/schema/catalog.jsonld
Metadata Catalog ID https://data.nasa.gov/data.json
Schema Version https://project-open-data.cio.gov/v1.1/schema
Catalog Describedby https://project-open-data.cio.gov/v1.1/schema/catalog.json
Homepage URL https://techport.nasa.gov/view/91437
Program Code 026:027
Source Datajson Identifier True
Source Hash 03fb25ea5e50d227c1aef971e64fe3da3312ac28
Source Schema Version 1.1

Didn't find what you're looking for? Suggest a dataset here.