Hyperspectral camera as a compact payload architecture for remote sensing applications

Author:

Morales-Norato David1ORCID,Urrea Sergio1ORCID,Garcia Hans1ORCID,Rodriguez-Ferreira Julian1,Martinez Elizabeth1,Arguello Henry1ORCID,Silva-Lora Alberto1,Torres Rafael1ORCID,Acero Ignacio F.2,Hernández Francisco L.3,Cárdenas Lorena P.4,Rincón Sonia4

Affiliation:

1. Universidad Industrial de Santander

2. Universidad Sergio Arboleda

3. Universidad del Valle

4. Fuerza Aérea Colombiana

Abstract

Monitoring and observation over the surface of the Earth have been a matter of global interest. In this path, recent efforts aim to develop a spatial mission to perform remote sensing applications. Mainly, CubeSat nanosatellites have emerged as a standard for developing low-weight and small-sized instruments. In terms of payloads, state-of-the-art optical systems for CubeSats are expensive and designed to work in general use cases. To overcome these limitations, this paper presents a 1.4 U compact optical system to acquire spectral images from a CubeSat standard satellite at the height of 550 km. To validate the proposed architecture, optical simulations using ray tracing simulation software are presented. Because the performance of computer vision tasks is highly related to data quality, we compared the optical system in terms of the classification performance on a real remote sensing application. The performances of the optical characterization and land cover classification show that the proposed optical system achieves a compact instrument, operating at a spectral range from 450 nm to 900 nm discretized on 35 spectral bands. The optical system has an overall f -number of 3.41 with a ground sampling distance of 52.8 m and a swath of 40 km. Additionally, the design parameters for each optical element are publicly available for validation, repeatability, and reproducibility of the results.

Funder

Ministerio de Ciencia Tecnología e Innovación

Fuerza Aerea Colombiana

Publisher

Optica Publishing Group

Subject

Atomic and Molecular Physics, and Optics,Engineering (miscellaneous),Electrical and Electronic Engineering

Reference42 articles.

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3. Small Satellites: Past, Present, and Future

4. Spectral imaging with deep learning

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