Abstract:This work derives and validates a noise model that encapsulates deadtime of non-paralyzable detectors with random photon arrivals to enable advanced processing, like maximum-likelihood estimation, of high resolution atmospheric lidar profiles while accounting for deadtime bias. This estimator was validated across a wide dynamic range at high resolution (4 millimeters in range, 17 milliseconds in time). Experiments demonstrate that the noise model outperforms the current state-of-the-art for very short time-of-flight (2 nanoseconds) and extended targets (1 microsecond). The proposed noise model also produces accurate deadtime correction for very short integration times. This work sets the foundation for further study into accurate retrievals of high flux and dynamic atmospheric features, e.g., clouds and aerosol layers.
Abstract:We demonstrate thermodynamic profile estimation with data obtained using the MicroPulse DIAL such that the retrieval is entirely self contained. The only external input is surface meteorological variables obtained from a weather station installed on the instrument. The estimator provides products of temperature, absolute humidity and backscatter ratio such that cross dependencies between the lidar data products and raw observations are accounted for and the final products are self consistent. The method described here is applied to a combined oxygen DIAL, potassium HSRL, water vapor DIAL system operating at two pairs of wavelengths (nominally centered at 770 and 828 nm). We perform regularized maximum likelihood estimation through the Poisson Total Variation technique to suppress noise and improve the range of the observations. A comparison to 119 radiosondes indicates that this new processing method produces improved temperature retrievals, reducing total errors to less than 2 K below 3 km altitude and extending the maximum altitude of temperature retrievals to 5 km with less than 3 K error. The results of this work definitively demonstrates the potential for measuring temperature through the oxygen DIAL technique and furthermore that this can be accomplished with low-power semiconductor-based lidar sensors.