A novel approach for estimation of residual attitude of a remote-sensing satellite

In this article, we establish an update procedure for rapid positioning coefficients or rational polynomial coefficients (RPCs) via iterative refinements using polynomial augmentation and reference images. RPCs are widely popular in establishing a ground-to-image relationship without using physical sensor model. However, the accuracies of RPCs are degraded due to unavoidable errors in physical sensor model based on colinearity conditions. These inaccuracies essentially arise due to undulating terrain, residual errors in attitude parameters, viz. roll, pitch and yaw, inexact modeling of drift and micro-vibration, orbit error, etc. In the paper, first an initial estimate of RPCs is obtained by using L 2 -regularized least square estimation. Subsequently, the RPCs are refined by using iterative affine augmentation. The RPC accuracy is further improved by a second-order polynomial augmentation. The results show that with the improved RPCs the average scan and pixel errors are within 0.5 pixel. The results of the paper are employed and validated on Resourcesat-2 imagery.

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“…1. Further details on ground-to-image transform can be found in Dubey and Kartikeyan (2018) and references therein.…”

Section: Ground-to-image Transformationmentioning

confidence: 99%

Rational Polynomial Coefficients Modeling and Bias Correction by Using Iterative Polynomial Augmentation

Dubey

Kartikeyan

Moorthi

2018

J Indian Soc Remote Sens

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A novel SLC to GEO image generation approach and automatic control points conversion from GEO to SLC domain for SAR data quality evaluation and analysis

Dubey

Kartikeyan

2022

Geocarto International

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Novel Residual Attitude Estimation Approach Using Georeferenced Satellite Imagery

Dubey

Kartikeyan

2022

photogramm eng remote sensing

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This article presents an efficient novel approach estimating residual attitude based on geometrically corrected (GEO ) satellite images. A technique is presented that uses orbital plane geometry to compute the rotation angle as a function of geographic latitude between GEO image space and radiometrically corrected (RAD ) image space. First, a nonlinear forward model is established that translates the residual errors in roll, pitch, and yaw to scan errors and pixel errors in GEO image space. Subsequently, the inverse problem is solved using Newton's method of nonlinear optimization for estimating residual roll, pitch, and yaw. We demonstrate our results on data products of the high-resolution Indian satellites Cartosat-2E and Cartosat-2F. Further, the superiority of the proposed method is established by comparing it with multiple existing methods in the literature. The R2 measures of goodness of fit for roll, pitch, and yaw estimation based on RAD and GEO products using the proposed method are 0.65, 0.99, and 0.65, respectively; using the existing method, they are 0.074, 0.005, and 0.50.

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A novel approach for estimation of residual attitude of a remote-sensing satellite

Cited by 3 publications

References 13 publications

Rational Polynomial Coefficients Modeling and Bias Correction by Using Iterative Polynomial Augmentation

Rational Polynomial Coefficients Modeling and Bias Correction by Using Iterative Polynomial Augmentation

A novel SLC to GEO image generation approach and automatic control points conversion from GEO to SLC domain for SAR data quality evaluation and analysis

Novel Residual Attitude Estimation Approach Using Georeferenced Satellite Imagery

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