2D signal estimation for sparse distributed target photon counting data.

In this study, we explore the utilization of penalized likelihood estimation for the analysis of sparse photon counting data obtained from distributed target lidar systems. Specifically, we adapt the Poisson Total Variation processing technique to cater to this application. By assuming a Poisson noise model for the photon count observations, our approach yields denoised estimates of backscatter photon flux and related parameters. This facilitates the processing of raw photon counting signals with exceptionally high temporal and range resolutions (demonstrated here to 50 Hz and 75 cm resolutions), including data acquired through time-correlated single photon counting, without significant sacrifice of resolution. Through examination involving both simulated and real-world 2D atmospheric data, our method consistently demonstrates superior accuracy in signal recovery compared to the conventional histogram-based approach commonly employed in distributed target lidar applications.

Nonlinear target count rate estimation in single-photon lidar due to first photon bias.

The use of time-tagging single-photon lidar for high-resolution ranging and backscattered count rate measurements requires special attention to mitigate biases and distortions typically not seen in full-waveform lidar sensors. Specifically, sub-pulse sampling and the presence of non-zero receiver dead-time generates an effect named first photon bias (FPB). FPB manifests itself as an intensity-induced ranging offset, previously documented, and a nonlinear count rate with integrated distribution distortions. These combined effects require special attention when integrating lidar point clouds to accurately estimate the backscattered signal strength and true range. This Letter indicates that correcting solely for the introduced range bias does not address the nonlinear shape distortions in the accumulated photon distribution. Analyses of distribution widths and estimated signal strengths must consider both effects. We present an analysis that demonstrates the cause and effect of the FPB on photon time-tagging integrated photon distributions using the Monte Carlo method, relates the modeled results to previously published data and statistics, and provides a framework for interpreting range and backscattered signal strength measurements from these sensors.

High resolution photon time-tagging lidar for atmospheric point cloud generation.

The application of time-correlated single photon counting hardware and techniques to atmospheric lidar is presented. The results establish the viability of adapting photon time-tagging techniques to atmospheric lidar systems, facilitating high-range resolution (millimeter-level precision) and dynamic system observing capabilities that address the variety of atmospheric scatterers often present in atmospheric lidar profiles. The technique is demonstrated through measurements made by a high repetition rate, low pulse energy, elastic scattering, photon counting lidar. Detection probabilities with a non-zero system dead-time are derived and tested using acquired data. Atmospheric point cloud generation and the statistical implications on data retrievals utilizing this approach are presented. The results show an ability to preserve backscattered intensities while generating photon detections at picosecond resolution from a variety atmospheric scatterers.

The Great Cold Spot in Jupiter's upper atmosphere.

Past observations and modeling of Jupiter's thermosphere have, due to their limited resolution, suggested that heat generated by the aurora near the poles results in a smooth thermal gradient away from these aurorae, indicating a quiescent and diffuse flow of energy within the subauroral thermosphere. Here we discuss Very Large Telescope-Cryogenic High-Resolution IR Echelle Spectrometer observations that reveal a small-scale localized cooling of ~200 K within the nonauroral thermosphere. Using Infrared Telescope Facility NSFCam images, this feature is revealed to be quasi-stable over at least a 15 year period, fixed in magnetic latitude and longitude. The size and shape of this "Great Cold Spot" vary significantly with time, strongly suggesting that it is produced by an aurorally generated weather system: the first direct evidence of a long-term thermospheric vortex in the solar system. We discuss the implications of this spot, comparing it with short-term temperature and density variations at Earth.

General description of polarization in lidar using Stokes vectors and polar decomposition of Mueller matrices.

Polarization measurements have become nearly indispensible in lidar cloud and aerosol studies. Despite polarization's widespread use in lidar, its theoretical description has been widely varying in accuracy and completeness. Incomplete polarization lidar descriptions invariably result in poor accountability for scatterer properties and instrument effects, reducing data accuracy and disallowing the intercomparison of polarization lidar data between different systems. We introduce here the Stokes vector lidar equation, which is a full description of polarization in lidar from laser output to detector. We then interpret this theoretical description in the context of forward polar decomposition of Mueller matrices where distinct polarization attributes of diattenuation, retardance, and depolarization are elucidated. This decomposition can be applied to scattering matrices, where volumes consisting of randomly oriented particles are strictly depolarizing, while oriented ice crystals can be diattenuating, retarding, and depolarizing. For instrument effects we provide a description of how different polarization attributes will impact lidar measurements. This includes coupling effects due to retarding and depolarization attributes of the receiver, which have no description in scalar representations of polarization lidar. We also describe how the effects of polarizance in the receiver can result in nonorthogonal polarization detection channels. This violates one of the most common assumptions in polarization lidar operation.

Polarization lidar for shallow water depth measurement.

A bathymetric, polarization lidar system transmitting at 532 nm and using a single photomultiplier tube is employed for applications of shallow water depth measurement. The technique exploits polarization attributes of the probed water body to isolate surface and floor returns, enabling constant fraction detection schemes to determine depth. The minimum resolvable water depth is no longer dictated by the system's laser or detector pulse width and can achieve better than 1 order of magnitude improvement over current water depth determination techniques. In laboratory tests, an Nd:YAG microchip laser coupled with polarization optics, a photomultiplier tube, a constant fraction discriminator, and a time-to-digital converter are used to target various water depths with an ice floor to simulate a glacial meltpond. Measurement of 1 cm water depths with an uncertainty of ±3 mm are demonstrated using the technique. This novel approach enables new approaches to designing laser bathymetry systems for shallow depth determination from remote platforms while not compromising deep water depth measurement.

Explicit description of polarization coupling in lidar applications.

Depolarization lidar requires discrimination of received power in polarized and unpolarized components of backscattered light. This can be accomplished with only two polarization measurements. However, parallel- and cross-polarization channels in depolarization lidar cannot always be regarded as independent, because system optical components can cause coupling between these channels and transmitter and receiver polarization planes are rarely perfectly aligned. Calibration constants, while in some instances reasonable approximations, do not fully describe the physics of the receiver and potential for coupling between orthogonal polarization modes. We present an analysis of a general receiver design and introduce an algorithm for decoupling the received data, which only requires the parallel- and cross-polarization data typically recorded in depolarization lidar measurements.