Adding SNR from multiple detectors

AI Thread Summary
When using two detectors with an SNR of 2 each, the overall SNR can improve if the signals are correlated and the noise is uncorrelated. The combined SNR is not simply additive; instead, it follows the root-sum-square method, resulting in an SNR of 2 times the square root of 2. This means that the fusion of the two detectors can enhance detection probability significantly. Understanding the correlation of signals and the nature of noise is crucial for accurate SNR calculations. Properly fusing data from multiple detectors can lead to better detection outcomes.
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I am looking at the same object with two detectors. The SNR on each is 2, which is a low probability of detect given a single sensor. However, if I fuse the two what would be the SNR then? Would it be additive (SNR=4) or rss (SNR=2×sqrt(2)) or something more complicated?
 
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Correlated signals add, uncorrelated signals are sqrt(sum of squares).

If the noise is uncorrelated between the detectors, and the signal is correlated, you will improve the SNR
 

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