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1.INTRODUCTIONFree-Space Optical Communications (FSOC) are foreseen to be the keystone of tomorrow’s fast, secure and low-latency worldwide data connection. Early demonstrators and commercial satellite fleets are currently being developed by several space agencies and industrial actors. Most of today’s development plans include a unique active feeder link aiming at a geostationary orbiting satellite (GEO) to avoid extra mechanical pointing challenges. Ground to satellite optical link requires knowledge of cloud coverage, absorption and turbulence to estimate a power budget, available bandwidth and an optimized data routing plan. If bad atmospheric conditions above active feeder degrades link’s quality, another feeder gateway, located 100’s of kilometres away with better parameters may be selected and a latency-free handover is triggered. Of the 3 aforementioned predominant phenomena in optical link quality degradation, turbulence is the less apparent but has a significant impact: a clear sky does not necessarily translates into a good optical propagation medium. Two major effects are produced by turbulence; Beam spreading is the widening of optical beam due to diffraction on turbulent eddies smaller than the beam waist. Such phenomena does not deviates the propagation path but increased the PSF, energy is spread over a larger area. Beam wandering is the deviation of optical beam due to refraction on turbulent eddies larger than the beam waist. Large convection cells induce step-index changes along great propagation distances, such as a GEO link. The laser beam is deviated from its aimed path. Fig. 1 proposes a representation of these effects, on a theoretical ground-to-GEO optical link. Figure 1:(Left) Beam-spreading mechanisms encountered by an FSOC link. A feeder station A aiming at satellite B through atmosphere C would have a narrow and aimed beam D without turbulence. Real eddies in both low and high altitude layers induce beam spreading and deviation E, challenging link quality. (Right) Representation of the real optical beam at satellite altitude. Speckles of radius Rs located at Rc from the theoretical centre may be observed, and all light might be ducted within radius RL.  Turbulence profile can be measured by bulky, expensive and active apparatus, such as radiosounding, LI-DAR, SODAR or instrumented towers. For site-selection and feeder station monitoring, we focused on a small, rugged, maintenance-free and low cost turbulence-profiler, as expected by telecom operators to probe a myriad of prospective locations without civil work. The SHAdow BAnd Ranger (SHABAR) is a well-acknowledged device for probing ground-layer turbulence profile during daytime, up to about a kilometre high. Several SHABAR have been employed for solar observatory site selection1,2 daylight seeing monitoring3 and lower-layer turbulence characterization456. Some devices, generically named LuSci, rely on the Moon scintillation to retrieve Prediction of atmospheric conditions over different ground stations for network planning is foreseen to be achievable through Machine Learning (ML) of large atmospheric databanks collected on-site by tens of sensors. Such ML-generated turbulence prediction based on previous records and large environmental databanks has already been tested on an astronomical observatory.7 Compact and rugged night turbulence monitor (C-DIMM), along with a day Sky-Scintillation Monitor (SSM) to retrieve Fried’s parameter are parts of our Integrated Sky Monitor (ISM), previously designed by Miratlas8 and operated by several research institutes. In our endeavour for reliable network planning and optical link quality optimization, we developed an autonomous daytime turbulence monitor probing sunlight’s scintillation to estimate local atmospheric refractive index structure parameter, commonly referred as In this paper, we will recall a short presentation of SHABAR’s work principle and applications in Sec.2. Our device development in the scope of FSOC will be described in Sec.3. Early results from 3 different locations will be assessed and commented in Sec.4. 2.SHABAR PRINCIPLEScintillation of starlight has long been employed as a quantitative measure of night seeing by astronomers. Because stars are ideal infinitely small emission points, their resulting scintillation index during high-altitude windy nights, can reach up to complete extinction due to beam wandering. Observation of stars’ point spread function (PSF) remains today’s easiest way to measure night-time seeing. During day-time, only the Sun may be used as a remote light source, but its large, finite diameter (about 960 arcsec) lead to significantly lower scintillation index, detectable with finely tuned electronics. Seykora9 concluded that Sun scintillation on a single pupil detector at Sacremento Peak observatory can be correlated to picture quality and, in fine, Fried’s parameter r0. Beckers10 proposed an expression to link solar scintillation where d is detector’s diameter, Ω is Sun’s diameter in radians, σi is irradiance fluctuation and h is observed layer’s height, ζ is the zenith distance. On a single-aperture detector, only an integrated r0 value, Fried’s parameter, can be determined. It is linked to Later, Beckers et al.12 reported the decreasing covariance of Sun’s scintillation, at ranging scintillometer spacing along a baseline. Fields of views of such detectors being strictly equal, different heights can be simultaneously probed for scintillation, hence outputting direct information on A schematic of basic SHABAR principle and geometry is depicted in Fig. 2. Figure 2:SHABAR principle: a baseline of scintillometers of diameter a is spaced evenly by length r. Measurements at height o display correlations as regions are being simultaneously probed.  Inversion of covariance data to retrieve an estimated 3.DESIGNA typical so-called “short-baseline” SHABAR consists of 6 scintillometers evenly placed into a sub-50cm long profiled aluminium beam. The U-shape of such beam ensures a high planar second moment of area, and reduces possible wind-induced vibrations, possibly detected as scintillation. The “detection-beam” is bolted on a dedicated az-alt mount designed for extreme weather conditions, water ingress protection and impact tolerance. Unlike other authors,3 we did not synchronized the tracking mount with a dedicated Sun-looking camera but to align roughly the tracker, as scintillometers’ large field of view tolerates misalignment of several degrees. Less than 50 W of installed power are necessary to run the tracker, instrumentation, computer and accessories. Between 2 movements of the tracker, each 10 seconds, power consumption is kept below 20 W so our SHABAR can run on solar-panels at remote locations. Raw and inverted data can be stored locally or sent over line-network (LAN). We also set-up a LTE-backed SHABAR so several inaccessible assessed places can be benchmarked in real-time. Figure 3:(Left) Main components of the turbulence profiler system, to retrieve a current  3.1Scintillation detectionMost SHABAR and LuSci devices relies on AC-coupled signal amplification and acquisition. Reliance on such configuration allows for high gains (ie: 1920 for Seykora et al.10) obtained various daisy-chained amplifiers, but also increase noise in the resulting digitized signal. Extreme weather conditions to be found at test facilities implies dramatic changes on capacitor and resistor values, even with low-temperature-drift components, biasing filter and amplifier responses. Finally, AC-coupling distorts and cuts-off very low frequencies that could be taken into account for upper-atmosphere characterization. For all these reasons, we decided, as previously done by Pfrommer et al.13 to implement a DC-coupled scintillometer baseline. By digitizing the whole, low-amplified signal on a high-precision Analog-to-Digital converter (ADC), we aim at performing an almost full-numerical filtering and amplification for a drift-less acquisition. Doing so challenges our acquisition chain noise performance, as Tokovinin et al.14 reported on a LuSci. Grounding, shielding of a transimpedance amplifier (TIA) and use of a quality ADC were also previously reported to be crucial for viability of DC-coupling system. Nethertheless, recent studies, from Hale et al.15 showed promising results for upper-atmosphere dust clouds measurements, and Sunlight extinction with a DC-coupled scintillometer. A quartz-windowed and metal-encased photodiode, with a 1mm2 active area has been chosen given its excellent Noise Equivalent Performance (NEP), around The self-developed TIA is built around a recent low-noise amplifier chip, reaching input voltage noise below 3.2Tracking mountA reliable, low-voltage and heavy-duty tracking mount is required for shipping, quick installation and harsh-environment operation over several months. We sourced and modified az-alt mount relying on high-ratio straight-gears and step-motors. Such mechanical assembly can sustain a 10 kg payload and display a 1 deg pointing precision on both axis. Position feedback is monitored via the sent step-motors pulses and is reset at each homing thanks to dead-end switches. Upon selection for production, the tracking mounts were exposed to direct Sunlight, UV-radiation, high-pressure water jets and condensing atmosphere during a week. Communication with the tracking mount is ensured by an embedded low-power micro-computer, generating a Graphical User Interface (GUI) for control, data output and maintenance procedures, as seen on Fig. 4. Because we do not include a Sun-tracking camera to save on computation power, a Network Time Protocol (NTP) is called every day, and checked against a battery-backed-up Real-Time Clock (RTC) module. Sun’s position is computed and updated every 10 seconds to lower vibration signals on the photodiodes. 3.3Inversion procedureFrom Inversion procedures were written in Python3 language for its ability to produce quality graphs, variety of signal-processing library and a short development time. A simplified yet straightforward description of Hill et al. theory is described in Sliepen et al. paper.3 Before processing inversion, raw data are digitally filtered to reject any unusable dataset. Theoretical Sunlight power is checked against each scintillometer response so defective or stained cells can be detected and discarded. Clouds, even thin cirrus, would skew a computed turbulence profile, are therefore checked against theoretical received power. If an ISM is located by the SHABAR, a ML algorithm detects clouds in the Sun vicinity and sets a rejection flag on the last dataset. If latest acquisition appear to be valid, it is pushed by secured-FTP to a local ISM for inversion procedure where it can be treated online or by batch. Resultant estimated 4.EARLY RESULTS4.1Raw data analysisAfter an extensive testing of electronic boards to ensure a noiseless data acquisition, a single scintillometer unit was set-up outside during winter 2022. Strong winds in lower and higher layers (Mistral wind), assorted with clear skies were assessed to tweak and optimize the acquisition chain in terms of amplifier and ADC bandwidth. As a last commissioning test, 6 scintillometers were set up in an electromagnetic (EM) shielded enclosure, without tracking mount, to assess possible EM-noise ingress over coaxial cables and TIA in the final SHABAR design. This shielded unit was powered with a 14.8 V Li-Po battery without active regulator, and data were collected on a personal computer powered on its battery. TIA supply voltage, dark and laser-illuminated scintillator signals shown a standard deviation of less than an 1 ADU on each channel, this corresponds to a solar scintillation signal σi of 6.62E-5, on a 5 V scale. No discrepancies between the 2 configurations were found, and our first batch SHABAR was declared usable. Tab. 1 sums-up datasets to be shown in the following section. Figure 6:(Left) SHABAR prototype at dawn by Saint-Véran observatory site, 3000 m high. (Right) Close-up view of the SHABAR prototype, installed on our office roof. All instrumentation is embedded in the rear water-tight enclosure.  Table 1:Dataset analysed in this publication.
Fig. 7 displays a typical Power Spectrum Density (PSD) obtained on 10000 Hanning windows when low-altitude wind is blowing (left) or not (right) at ground layer. If strong wind gusts of convection are encountered, scintillation power spectra display a clear increase in higher frequencies signal strengths. Steep decrease visible on the rightmost part of Fig. 7a reach up to 12 dB/decade, but the “tipping point” with a 1/f noise signal on the leftmost part, seems to vary consequently with lower-layer turbulences. Plotting autocorrelation of the same data, Fig. 7b, reveals clear and straight structures, coherent with a slowly-varying envelope signal. Conversely, scintillations observed under wind gusts or strong convection due to intense Sunlight on a dark roof induce a lower, if any, autocorrelation curve. On Fig. 8, moving-mean averaged Sunlight intensities were plotted on 2 extremes cases, namely AQ2 and AQ5, to identify low-frequency patterns. Smoothing is operated on a 500 ms segment on each of the 6 photocells to show similarities and lag. Figure 9:Correlation matrices of the 6 scintillometers, during 4 acquisitions at Saint-Véran observatory site.   Large low-frequency oscillations of Fig. 8(up), with a ≈ 1 s period envelop smaller, high-frequency signal variations, smoothed by the moving-mean filter. Under a pristine sky, with r0 reaching 20 cm on Fig. 8(down), the strong coherence between each photodiode signal is visible, but the large signal fluctuation in the mHz range is tracked thanks to DC-coupling and filter-less acquisition system. 4.2Cn2 profile restorationCorrelation coefficients between each detector time-series are displayed Fig. 9 for four acquisitions separated by 10 minutes, on a summer noon at Saint-Véran observatory. A single, direct output 5.CONCLUSIONA day-time turbulence profiler has been designed and field-tested in the frame of Free-Space Optical Communications (FSOC). Its passive, low-power and autonomous operation targets remote-location probing for site-selection and data routing optimization. REFERENCESSocas-Navarro, H., Beckers, J., Brandt, P., Briggs, J., Brown, T., Brown, W., Collados, M., Denker, C., Fletcher, S., Hegwer, S.,
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