Gravitational lensing is the effect on a lightlike trajectory by the presence of matter, affecting its trajectory in spacetime. Gravitational lensing of gravitational waves can occur in geometric optics limit (when GW wavelength is much smaller than the Schwarzschild radius of the lens i.e. $\lambda_{GW} \ll$ R$^{\rm sc}_{\rm lens}$, multiple images with different magnifications are formed) known as strong-lensing or in wave optics limit (when the wavelength of GW is larger than the Schwarzschild radius i.e. R$^{\rm sc}_{\rm lens}$ $\lesssim \lambda_{GW} $, interfering signals produce beating pattern in the waveform envelope) known as micro-lensing. Currently, large sky-localization errors of GW sources and strong noise-PSD have barred us from evidencing lensed GWs. Considering this aspect, we have developed $\texttt{GLANCE}$, a novel technique to detect lensed GWs. We demonstrate that cross-correlation between the data pieces containing lensed signals shows a very specific trend. The strength of the cross-correlation signal can quantify the significance of the event(s) being lensed. Since lensing impacts the inference of the source parameters, primarily the luminosity distance for the strong lensing case, a joint parameter estimation of the source and lens-induced parameters is incorporated in $\texttt{GLANCE}$ using a Bayesian framework. We applied our method to simulated strongly lensed data and we have shown that $\texttt{GLANCE}$ not only can detect lensed GW signals but also can correctly infer the injected source and lens parameters even when one of the signals is below the match-filtered threshold SNR. This demonstrates the capability of $\texttt{GLANCE}$ for a robust detection of lensed GW signal from noisy data.
Comment: 16 pages, 23 figures (including appendices)