SNR-opt

This is for sharing codes (MATLAB) used in

S. Kim, A. Sharma, Y. Y. Liu and S. I. Young, "Rethinking Satellite Data Merging: From Averaging to SNR Optimization," in IEEE Transactions on Geoscience and Remote Sensing, vol. 60, pp. 1-15, 2022, Art no. 4405215, doi: http://dx.doi.org/10.1109/TGRS.2021.3107028

Code description

The codes consist of nine MATLAB scripts and a brief explanation for each one is as follows.

Two main scripts in which four merging methods (weighted averaging, SNR-opt, maxR, unweighted averaging) are compared

1. mergingExample_the.m: an example to merge three (or any number) synthetic zero mean datasets (no time series).
2. mergingExample_syn.m: an example to merge three (or any number) synthetic zero mean datasets (time series).

Seven functions used in the main scripts

1. WA.m: to calculate merging coefficients for weighted averaging.
2. SNRopt.m: to calculate merging coefficients for SNR-opt.
3. maxR.m: to calculate merging coefficients for maxR (maximizing correlation).
4. SNRest.m: to estimate noise-to-signal ratio and scaling factor for given covariance matrix and signal power (any number of products).
5. ECVest.m: to estimate error covariance matrix and data-truth correlation for given covariance matrix (any number of products). This is equivalent to Triple Collocation but produces no failures and is applicable for any number of products.
6. EeeTGEN.m: to generate error covariance matrix for given number of products and error cross-correlation
7. dataGEN.m: to generate orthogonal y (truth) and e (error) for given data length, number of products, error cross-correlation, and signal-to-noise ratio