Atmospheric visibility sensor based on backscattering using correlation coding method

Tomasz Czarnecki Krzysztof Perlicki Grzegorz Wilczewski An new atmospheric visibility sensor is described which uses an empirical relationship between atmospheric visibility and lidar backscatter signals. Specifically, autocorrelation analysis is performed for lidar backscatter signals and the autocorrelation coefficients are shown to be a function of the correlation distance. The slope of this function is then connected to the atmospheric visibility under different weather conditions. It is experimentally demonstrated that this new sensor can reliably estimate the atmospheric visibility in the range of 0-1,200 m. - A clear visibility of the surrounding environment is crucial in various types of transportation means. Dense fog or rain developed alongside roadways may considerably decrease the safety of motorists, thus automated detectors and monitoring of the visibility, fog, rain, snow or dust is of the upmost importance. As a feasible variable, atmospheric visibility is difficult to assess. Weather, sun angle, light intensity, darkness adaptation, availability of appropriate visibility targets and individual physical abilities determine the level of humans perception quality of atmospheric conditions. Automated visibility sensors determine the visibility range by measuring light being scattered or by utilization of extinction coefficients, locally over a short range (Siikamaki 2004; Babari et al. 2011). Optical sensors such as transmissometers or scatterometers were developed to address atmospheric visibility and visual range evaluation. The transmissometer was the first instrument developed to provide a standard for visibility measurement. The device estimates the attenuation of a light beam emitted from a source to a receiver at a certain path length and correlates obtained result with human observations. The light attenuation phenomena is due to scattering or refraction, depending on the utilized medium. However, transmissometers physical dimensions and long baselines create a multiplicity of disadvantages when performance is considered. Demanding maintenance, high manufacturing costs and small dynamic range with insufficient accuracy discard transmissiometers from being abundantly popular. In case of the scatterometer, measurements are based on the amount of light being scattered by aerosols in an optical volume, observed within a small solid angle. The scatterometer assesses the dispersion of a light beam (Kazovsky 1985; Kemp et al. 2012), nevertheless reliability of a typical scatterometer is reported as questionable (Babari et al. 2011). Atmospheric visibility assessment is also performed with the use of light backscattering phenomenon (Taillade et al. 2008). Therein discussed is the thoroughly performed examination of the analytical model supporting backscattered luminance investigation (with an optical device geometry modeling), and as authors report, a good performance in agreement with experimental results. Another approach towards cruise supporting systems (Hautiere et al. 2008), with respect to the vehicular transportation domain, shows several visual data analysis approaches to enable estimation of the atmospheric visibility in mobile applications, with low margin of error. In this paper, a brand new method for atmospheric visibility estimation is depicted. Presented sensor setup employs light backscattering effect with use of correlation coding technique. Evaluation of atmospheric visibility range is performed by signal correlation analysis. 2 Methodology 2.1 Atmospheric visibility estimation based on backscattering using correlation coding technique The principle of operation of the designed sensor is based on the analysis of backscattered optical signal. Devices transmitter emits an optical signal into the air where the light is subjected to backward scattering by air particles (for instance: rain drops, snowflakes or fog) and arrives at the receiver where it falls onto a photodetector. The backscattered optical signals within a range from 0 to 250 m are being analyzed. The principle of operation of the presented sensor is depicted on the schematic diagram in the Fig. 1. Consequently, the setup configuration of the described device is shown in the Fig. 2. Concerning architectural layout of the presented sensor, it is composed of transmitting and receiving parts. The transmitting module generates pulsed laser light with the wavelength of 808 nm and the average optical power of 250 mW (the Bob 808-2W laser is utilized). The optical signal generated consists of a 7.5 Mbit/s binary stream with 29 1 length of Pseudo Random Bit Sequence (PRBS). As presented on the Fig. 1, characteristic of emitted radiation is described as nearly parallel as it concentrates in a form of a regular beam with the diameter equal to 50 mm. Transmitting beam intersects with the receiving one at a distance of 250 m (what further implies the zone taken under consideration in autocorrelation analysis) from the surface of both active parts. In terms of the divergence, the receiving beam parameter is equal to approximately 1 of the angular spread, while the receiver area diameter is 120 mm. At the receiving end, the avalanche photodiode Hamamatsu C5331-02 (APD module on the Fig. 1) and 808 nm narrow bandpass optical filter are used. In order to sustain reliable measurements, Fig. 2 The atmospheric visibility sensorsetup layout it is of the upmost importance to prevent the receiver from falling into a saturation mode. Sensor parameters (i.e.: the laser optical power, photodiode active area size, analog to digital converter dynamic range) have been precisely selected, as it is crucial to avoid saturation state of the receiving part. To complete the description of the designed device, the transmitting part consists of the pushpull power driver and synchronization branch towards the wave generator. Receiving section utilizes HYPRES HA103-35 signal amplifier and 16-bit analog to digital converterADC 08L060. To organize the workflow, PIC 16F630 microchip is applied to support the control functions, as well as communication with outer devices by means of Universal Serial Bus (USB). Further, concerning methodology insights, as it is presented on the plots within Fig. 3, stream autocorrelation versus correlation distance for different weather conditions (i.e. atmospheric visibility) is assessed. On the figure, the plots to the left side depict the behavior 1,0 ten 0,9 ii ffc 0,8 e co 0,7 n ito 0,6 a l rre 0,5 tcuooA 00,,34 0,2 0,1 0,0 t 1,0 ien 0,9 ffc 0,8 i e co 0,7 n ito 0,6 a l rre 0,5 tcoouA 00,,43 0,2 0,1 0,0 1,0 ten 0,9 ii ffc 0,8 e co 0,7 n ito 0,6 a l rre 0,5 tcuooA 00,,34 0,2 0,1 Fig. 3 Autocorrelation coefficient versus correlation distance under different weather conditions (atmospheric visibility) of the autocorrelation coefficient, as a function of considered distance, reflecting the outdoor atmospheric conditions (as presented by the stacked images to the right). (...truncated)