The simplest signal to characterize is a long-lasting periodic signal with a given fixed frequency . In an observation time T, all the signal power is concentrated in a single frequency bin of width . The noise against which it competes is just the noise power in the same bin, . The power SNR is then , and the amplitude SNR is . This improves with observation time as the square root of the time. The reason for this is that the noise is stationary, but longer and longer observation times permit the signal to compete only with noise in smaller and smaller frequency windows.
Of course, no expected gravitational-wave signal would have a single fixed frequency in the detector frame, because the detector is attached to the Earth, whose motion produces frequency modulations. But the principle of this SNR increase with time can still be maintained if one has a signal model that allows one to exclude more and more noise from competing with the signal over longer and longer periods of time. This happens with matched filtering, which we return to in Section 5.
Short-lived signals have wider bandwidths, and long observation times are not relevant. To characterize their SNR, it is useful to define the dimensionless noise power per logarithmic bandwidth, , which we earlier called . The signal Fourier amplitude has dimensions of Hz–1 and so the Fourier amplitude per logarithmic frequency, which is called the characteristic signal amplitude , is dimensionless. This quantity should be compared with to obtain a rough estimate of the SNR of the signal: SNR .
This work is licensed under a Creative Commons License.