A flux calibration method for remote sensing satellites using stars

TL;DR

This paper proposes a star-based flux calibration method for remote sensing satellites using a mini-camera, achieving approximately 2% calibration accuracy by observing stars and ground objects alternately.

Contribution

It introduces a novel star-based calibration approach employing a mini-camera on satellites, enabling high-precision flux calibration of remote sensing instruments.

Findings

Achieves about 2% calibration accuracy.

Utilizes stars with stable fluxes as calibration standards.

Employs a mini-camera for simultaneous star and ground observation.

Abstract

Star surveys and model analyses show that many stars have absolute stable fluxes as good as 3% in 0.3-35{\mu}m wavebands and about 1% in the visible wavebands. The relative flux calibrations between stars are better than 0.2%. Some stars have extremely stable fluxes and can be used as long term flux calibration sources. Stellar brightness is several orders of magnitude lower than most ground objects while the stars do not usually appear in remote sensing cameras, which makes the stars inappropriate for being calibration sources. The calibration method using stars discussed in this paper is through a mini-camera attached to remote sensing satellite. The mini-camera works at similar wavebands as the remote sensing cameras and it can observe the stars and the ground objects alternatively. High signal-to-noise ratio is achieved for the relatively faint stars through longer exposure time. Simultaneous precise cross-calibration is obtained as the mini-camera and remote sensing cameras look at the ground objects at the same time. The fluxes from the stars used as calibration standards are transferred to the remote sensing cameras through this procedure. Analysis shows that a 2% accurate calibration is possible.