## 5 Discussion  
As a result, different algorithms (Figure 6) were applied to calculate reflectograms for the same data set corresponding to one spectral scan. In this case, the measurement time was fixed automatically for all of the calculated reflectograms. Nevertheless, we tried to model the reflectograms evaluation for measurements with shorter pulses. In particular, we compared reflectograms with different numbers of averaging points, simulating a change in the duration of mode pulses, (4.1) and averaging over a set of traces obtained using different time intervals for the same pulses, (4.2). As a result, it can be concluded that this type of the averaging procedure significantly affected the character of the final trace. The order of normalization and averaging procedures had a strong influence on the NFL. The NFL after averaging 10 reflectograms is \(\sim\)3 dB higher than after regular time-domain accumulation of the signal (while keeping the total value of data points fixed). This result can be associated with the fact that the normalization procedure was not commutative with averaging and FFT. However, fluctuations in the reflectograms at coordinates corresponding to the noises decreased when averaging over 10 reflectograms corresponding to different of measured signals were used (red line in Figure 8). The useful signal (corresponding to RLS or point reflectors) remains constant in the case of temporal averaging, regardless of the normalization order. This result must be connected to the fact that the reflectograms calculated from different sections of the mode pulse are equivalent due to the preservation of the spectral and phase properties of the self-sweeping laser throughout the generation of each pulse. However, the signal level begins to increase significantly when the number of averaging points decreases to \(\sim\)1-2 due to the excess in the NFL level over the RLS level. It should be noted that in the OFDR systems based on pulsed self-sweeping lasers [19], the number of points used for the signal accumulation and reflectograms calculation was relatively small (-5) due to the short duration of each pulse. In the present work, a continuous-wave self-sweeping laser with generation of long (\(\sim\)few milliseconds) single-frequency pulses was used. In this case, there is a possibility for long signal accumulation for calculation of a single reflectogram. This outcome eliminates both the need for synchronization of measurements of different scans, which is typical for faster seeping with shorter pulses, and the problem of optical frequency stabilization during slow sweeping, because both the frequency tuning step and generation frequency set are fixed in our case. In addition, the generation of long pulses opens the possibility of signal accumulation for each frequency. It has been shown that time domain averaging makes it possible to significantly (up to \(\sim\)30 dB) reduce the NFL when the number of points is increased from 1 to \(\sim\)450 (i.e., by \(\sim\)27 dB). It can be expected that if the system noises are dominated by the amplitude ones, the NFL should be proportional to a square root of the number of averaging points, i.e., the NFL slope as a function of the number of averaging points should be \(\sim\)0.5 dB/dB [24]. On the other hand, the reflectograms are calculated as the FFT amplitude (20 log instead of the usual 10 log), hence the slope should be 1 dB/dB instead of 0.5 dB/dB. Nevertheless, Figure 8b shows non-linear dependence with a higher slope of 2 dB/dB at a small number of averaging points and smaller slope (down to 0.5 dB/dB) for a larger number of averaging points. The slope reduction itself can be interpreted as saturation when the nature of dominant noises becomes different (e.g., the noises related to the bit depth of the signal digitalization). Moreover, the smaller decrease slope for the NFR may be related to the effect of the normalization procedure. This issue requires further research.