Return Signal Research Articles

Differential absorption lidar data acquisition and control system for remote detection of trace chemicals including methane and thiodiglycol.

We report the design and development of a data acquisition and control system for high-speed acquisition of weak, backscattered differential signals and synchronized sequential operation of all subsystems of a tunable, mid-infrared Differential Absorption Lidar (DIAL) system. The presence of a low-level concentration of chemical species results in weak differential return signals. The differential signal also varies dynamically with respect to background atmospheric conditions. The challenge is to measure this low level of differential signal with high resolution and also control the sequence of operation of subsystems such as lasers and scanners for real time testing and evaluation in open field conditions. The concentration spread of the chemical species varies rapidly with distance. In order to capture this spatial variation, the lidar signal should be sampled and digitized at a high sampling rate. A customized Peripheral Component Interconnect based data acquisition of a 12-bit resolution, 30 Mega samples per second sampling rate, and an industrial personal computer-based control system has been realized. Detection algorithms and the firing sequence of the laser have been developed indigenously and implemented in the LabVIEW platform. The developed graphical user interface has various modes of operation as per user requirement and is capable of executing automatic operations for the developed DIAL system in order to detect and identify the chemicals. The performance has been evaluated by detecting the chemical species thiodiglycol at 800m using 3190 and 3300nm (online and offline wavelengths) with a differential cross-section of 2.5 × 10-23m2. Similarly, methane has been detected and quantified with concentration of 2.2 ppm up to 300m using 3316 and 3326nm (online and offline wavelengths, respectively).

Development of mobile lidar for remote sensing of tropospheric ozone on the vertical and horizontal (slant) paths

We present a mobile lidar for measuring, in the ultraviolet (UV) region of the spectrum, the spatial distribution of ozone (O3) in the troposphere on the vertical and horizontal (slant) sensing paths, using the four-channel system of recording the return signals. The lidar operates, based on the lidar differential absorption and scattering method on the wavelength pair of 299 nm and 341 nm. We present a technical description of the lidar developed.

A Novel MIMO-SAR Echo Separation Solution for Reducing the System Complexity: Spectrum Preprocessing and Segment Synthesis

The problem of echo separation using digital beamforming (DBF) on receive for multiple-input multiple-output (MIMO) synthetic aperture radar (SAR) is of notable importance to allow for practical systems. Regrettably, current DBF-MIMO-SAR schemes, such as the short-term shift-orthogonal (STSO) scheme, are computationally cumbersome, increasing the required hardware complexity. To alleviate this problem, we here propose an improved echo separation solution for realizing a low-cost MIMO-SAR system. We detail a generic waveform design scheme as well as optimized monostatic radar waveforms (e.g., nonlinear frequency modulation (NLFM) signal) showing how these can be directly adopted in the proposed scheme to improve the imaging performance. The proposed scheme enables the number of the interference segments generated by unmatched waveforms to be halved by the use of the fast time spectrum preprocessing and segment synthesis, dramatically simplifying the array configuration and reduces the system complexity. By exploiting inter-pulse phase coding techniques, the proposed method can provide a reconfigurable waveform transmitting scheme, allowing the system resources in range frequency, elevation space, and Doppler domains to be jointly exploited for the separation of aliased signal returns. The proposed scheme is evaluated using extensive numerical and measured data sets, demonstrating the feasibility and potential of the proposed method for resource-limited spaceborne/airborne MIMO-SAR systems.

Simulation Study of the Applicability of the “Slice” Approach to Assessing the Water Content in Clouds from the Radar Return Signal

By computer simulation, the main consequences of the “slice” approach to assessing the power of a radar return signal from an atmospheric water cloud were verified. The cloud was modeled as a set of slices, which are thin layers coinciding with the wavefront of the probing radar radiation. The return signal was calculated as the convolution of the probe pulse with the cloud. The simulation was based on the previously derived “slice” radar equation, which determines the received power taking into account the statistical characteristics of fluctuations in the number of slice droplets and their water content. Estimates of the magnitude of the simulated return signal were compared with the theoretical formula for various statistical characteristics of the ensemble of droplets that make up the cloud model. The simulation result confirmed the validity of using the slice approach to interpret radar measurements of water content in clouds.

Return freight insurance strategies for the online retailer and insurance company

In online purchases, customers often exhibit considerable hesitations due to quality uncertainty and return freight fees. In response, online retailers may buy the return freight insurance (RFI) service from insurance companies that compensate the customers when they return the purchased item. With the RFI service, insurance companies generally verify the quality information posted by the retailer to avoid excessive customer returns. Thus, the RFI service not only reduces the customer’s return freight but also acts as an imperfect quality signal for customers to mitigate quality uncertainty. We characterize the RFI’s imperfect signaling effect by signal efficiency, and develop a game-theoretic model to investigate the RFI strategies of insurance companies and the retailer. Our results shed light on how signal efficiency and return freight fees drive their RFI strategies. The insurance companies charge an extremely small RFI premium for the retailer selling high-quality products; for the retailer selling low-quality products, the RFI premium becomes large for those with a medium return freight fee, or with a small signal efficiency. The retailer selling high-quality products always adopts the RFI service. The retailer selling low-quality products does not adopt the RFI service when the return freight fee is large. Given a medium return freight fee, the retailer with low-quality products prefers the RFI service when the signal efficiency is medium. Given a small return freight fee, only when the signal efficiency is large does the retailer with low-quality products adopt the RFI service. Our results provide new explanations for the prevalence of the RFI service for retailers selling products of different quality, and shed light on the RFI premium strategy for insurance companies.

The Role of Phytoplankton Biomacromolecules in Controlling Ocean Surface Roughness

Satellite altimetric data routinely map sea surface topography by measuring the ocean return signal. One source of altimeter measurement contamination occurs when the radar ocean backscatter becomes unusually large, a situation termed a Sigma-0 bloom. Past research suggests Sigma-0 blooms are associated with weak wind and natural surface slick conditions where capillary waves at the air–sea interface are suppressed. To date, no explicit connection between these conditions and Sigma-0 bloom presence has been provided. Using a series of simplified equations, our reduced model determines capillary wave heights from estimates of planktonic carbon concentrations and regional wind speed. Our results suggest that the radar signal reflection increases as capillary wave height decreases. This relationship depends on surfactant concentration, surfactant composition, and wind speed. Model sensitivity analysis indicates that the interface reflectivity depends on biological activity and wind speed. Our proposed simplified model provides a method to identify potential Sigma-0 bloom regions. We conclude that because of the demonstrated impact of biological surfactants on ocean roughness, it is necessary to consider the biological activity, i.e., phytoplankton bloom events, when interpreting signals from radar altimetry and when developing ocean hydrology models.

The Death of Active Management Has Been Greatly Exaggerated

Over the past decade, the asset management industry witnessed a significant migration of capital from active investment strategies into passive investment strategies. Undoubtedly, the structural change is shaking the active management–dominated mutual fund industry to its core. A closer scrutiny of active management suggests that the performance of active managers is mainly a function of both stock selection and portfolio construction. As other studies have already provided evidence of successful stock selection strategies via factor premiums, the author focuses on examining the impact of portfolio construction on portfolio performance. The author finds that active managers’ failure to incorporate risk during portfolio construction overwhelms the expected return signal from stock selection.

EXTRACTION OF ROAD MARKINGS FROM MLS DATA: A REVIEW

Abstract. Nowadays, Mobile Laser Scanning (MLS) systems are more and more used to realize extended topographic surveys of roads. Most of them provide for each measured point an attribute corresponding to a return signal strength, so called intensity value. This value enables to easily understand uncolored MLS as it helps to differentiate materials based on their albedo. In a road context, this intensity information allows to distinguish, among others, the main subject of this paper, i.e. road markings. However, this task is challenging. Road marking detection from dense MLS point cloud is widely studied by the research community. It might concern road management and diagnosis, intelligent traffic systems, high-definition maps, location and navigation services. Dense MLS point clouds provided by surveyors are not processed online, they are thus not directly applicable to autonomous driving, but those dense and precise data can be for instance used for the generation of HD reference maps. This paper presents a review of the different processing chains published in the literature. It underlines their contributions and highlights their potential limitations. Finally, a discussion and some suggestions of improvement are given.

Novel Simulation and Analysis of Mie-Scattering Lidar for Detecting Atmospheric Turbulence Based on Non-Kolmogorov Turbulence Power Spectrum Model.

The Mie-scattering lidar can detect atmospheric turbulence intensity by using the return signals of Gaussian beams at different heights. The power spectrum method and Zernike polynomial method are used to simulate the non-Kolmogorov turbulent phase plate, respectively, and the power spectrum method with faster running speed is selected for the subsequent simulation. In order to verify the possibility of detecting atmospheric turbulence by the Mie-scattering lidar, some numerical simulations are carried out. The power spectrum method is used to simulate the propagation of the Gaussian beam from the Mie-scattering lidar in a vertical path. The propagation characteristics of the Gaussian beam using a non-Kolmogorov turbulence model are obtained by analyzing the intensity distribution and spot drift effect. The simulation results show that the scintillation index of simulation is consistent with the theoretical value trend, and the accuracy is very high, indicating that the method of atmospheric turbulence detection using Mie-scattering lidar is effective. The simulation plays a guiding role for the subsequent experimental platform construction and equipment design.

Elastic LIDAR Monitoring of the Night-sky Brightness over Roque de los Muchachos Observatory

Every large world-class observatory must operate in a very dark environment that is as free as possible of anthropogenic sources of light pollution, which can degrade the quality of ground-based astronomical observations. A LIDAR is able to measure, and subtract from its laser return signals, a corresponding contribution from the night-sky brightness. Our elastic LIDAR system is operated in semi-continuous mode at night, very closely following the observation schedule of the MAGIC Telescopes on Canary island La Palma, Spain. For the monitoring of the night-sky brightness, median LIDAR background rates at different atmospheric conditions and sky illuminations have been used. In this talk, results from data taken with the MAGIC LIDAR over seven years, from March 2013 until March 2020, will be presented and discussed.

Complementarity of wind measurements from co-located X-band weather radar and Doppler lidar

Abstract. Accurate wind profile measurements are important for applications ranging from aviation to numerical weather prediction. The spatial pattern of winds can be obtained with ground-based remote sensing instruments, such as weather radars and Doppler lidars. As the return signal in weather radars is mostly due to hydrometeors or insects, and in Doppler lidars due to aerosols, the instruments provide wind measurements in different weather conditions. However, the effect of various weather conditions on the measurement capabilities of these instruments has not been previously extensively quantified. Here we present results from a 7-month measurement campaign that took place in Vantaa, Finland, where a co-located Vaisala WRS400 X-band weather radar and WindCube 400S Doppler lidar were employed continuously to perform wind measurements. Both instruments measured plan position indicator (PPI) scans at 2.0∘ elevation from the horizontal. Direct comparison of radial Doppler velocities from both instruments showed good agreement with R2=0.96. We then examined the effect of horizontal visibility, cloud base height, and precipitation intensity on the measurement availability of each instrument. The Doppler lidar displayed good availability in clear air situations and the X-band radar in precipitation. Both instruments exhibited high availability in clear air conditions in summer when insects were present. The complementary performance in the measurement availability of the two instruments means that their combination substantially increases the spatial coverage of wind observations across a wide range of weather conditions.

4 days in dry immersion increases arterial wall response to ultrasound wave as measured using radio-frequency signal, comparison with spaceflight data.

Recent studies have reported a significant increase in common carotid artery (CCA) intima media thickness, wall stiffness and reflectivity to ultrasound, in astronauts, after six months of spaceflight. The hypothesis was that 4 days in dry immersion (subjects under bags of water) will be sufficient to change the CCA wall reflectivity to ultrasound similar to what observed after spaceflight. Such response would be quantified using the amplitude of the ultrasound signal returned to the probe by the target concerned. [coefficient of signal return (Rs)]. The Rs for anterior and posterior CCA wall, sternocleidomastoid muscle, intima layer and CCA lumen were calculated from the ultrasound radio frequency (RF) data displayed along each echographic line. After four days of DI, Rs increased in the CCA posterior wall (+15% +/- 10 from pre DI, p < 0.05), while no significant change was observed in the other targets. The observed increase in Rs with DI was approximately half compared to what was observed after six months of space flight (+34% +/- 14). This difference may be explained by dose response (dry immersion only four days in duration). As a marker of tissue-level physical changes, Rs provide complimentary information alongside previously observed CCA wall thickness and stiffness.

Automating the Acoustic Detection and Characterization of Sea Ice and Surface Waves

Monitoring the status of Arctic marine ecosystems is aided by multi-sensor oceanographic moorings that autonomously collect data year-round. In the northeast Chukchi Sea, an ASL Environmental Sciences Acoustic Zooplankton Fish Profiler (AZFP) collected data from the upper 30 m of the water column every 10–20 s from 2014 to 2020. We here describe the processing of the AZFP’s 455 kHz acoustic backscatter return signal for the purpose of developing methods to assist in characterizing local sea ice conditions. By applying a self-organizing map (SOM) machine learning algorithm to 15-min ensembles of these data, we are able to accurately differentiate between the presence of open water and sea ice, and thereby characterize statistical properties surface wave height envelopes and ice draft. The ability to algorithmically identify small-scale features within the information-dense acoustic dataset enables efficient and rich characterizations of environmental conditions, such as frequency of sparse ice floes in otherwise open water and brief open-water leads amidst the ice pack. Corrections for instrument tilt, speed of sound, and water level allow us to resolve the sea surface reflection interface to within approximately 0.06 ± 0.09 m. By automating the acoustic data processing and alleviating labor- and time-intensive analyses, we extract additional information from the AZFP backscatter data, which is otherwise used for assessing fish and zooplankton densities and behaviors. Beyond applications to new datasets, the approach opens possibilities for the efficient extraction of new information from existing upward-looking sonar records that have been collected in recent decades.

Methods and Algorithms of Subsurface Holographic Sounding

In our experiments, we develop and test portable multi-element receiver antenna arrays, electrically scanned in order to immediately obtain a recognizable image of subsurface objects. Two quadrature components of the radar return signal are processed with a Kirchhoff backward migration algorithm. Physical theory is used to assess the quality of the holographic image, and the synthetic aperture approach is developed and tested. The parabolic wave equation and Gaussian beam technique are used in order to take into account refraction effects and to suppress specular reflection from the air-ground interface. Laboratory and field tests confirmed the predicted device parameters.

Mapping Samudra Tapu glacier: A holistic approach utilizing radar and optical remote sensing data for glacier radar facies mapping and velocity estimation

Himalayan glaciers have shown more sensitivity and visible changes to the climate change and global warming in the last 150 years. The highly rugged topography and inaccessible remote areas makes satellite images as the most appropriate source of information retrieval. We performed remote sensing based glacier change study for Samudra Tapu glacier, located in the Chandra basin of North-West Himalaya. In the present study, the capabilities of both optical and microwave remote sensing data was analysed in glacier change study in terms of its coverage, shift in equilibrium line altitude (ELA) and surface velocity over a period from 2000 to 2021. Multi Sensor (RISAT-1, Sentinel-1) time series of C-band SAR data along with a object oriented classification technique were used to identify different glacier facies such as percolation facies, icefalls, bare ice facies, refreeze snow and supraglacial debris. These classified maps were also used to detect the snow line and firn line along with ELA, aided with elevation information from digital elevation model (DEM). It was identified that more than 50 % of the total glacier area still lies into accumulation region. Further, we estimated the glacier surface velocity using Differential Interferometric Synthetic Aperture Radar (DInSAR) technique using European Remote Sensing Satellite (ERS-1/2) tandem data of 1996. High value of coherence was observed from the SAR return signal for one-day temporal difference. A mean velocity of 17–24 cm/day was found for the months of March and May 1996, highest flow rates were seen in the high accumulation area located in the Eastern and Southern Aspect of glacier. Spatial analysis of velocity patterns with respect to slope and aspect show that high rates of flow was found in southern slopes and movement rates generally increase with increase in slope. Feature tracking approach was used to estimate the glacier flow for long term and seasonal basis using optical and SAR datasets (IRS-1C, 1D PAN, Landsat-7, 8 PAN, and TANDEM-x) during 1999–2020 period. The results suggest that glacier flow varies with season, i.e., high velocity during spring-summer season, as compared to late summer or winter and, the rate of ice flow changes over the years. The mean glacier velocity reduced to 49.5 m/year during 2013–2020 time, as compared to 67.67 m/year during 1999–2003 time. These results of reducing glacier velocity and changing snow line altitude indicates enhanced glacier’s melt rate and overall negative mass balance for Smudra tapu glacier.

A Novel Lidar Signal-Denoising Algorithm Based on Sparrow Search Algorithm for Optimal Variational Modal Decomposition

Atmospheric lidar is susceptible to the influence of light attenuation, sky background light, and detector dark currents during the detection process. This results in a large amount of noise in the lidar return signal. To reduce noise and extract a useful signal, a novel denoising method combined with variational modal decomposition (VMD), the sparrow search algorithm (SSA) and singular value decomposition (SVD) is proposed. The SSA is used to optimize the number of decomposition layers K and the quadratic penalty factor α values of the VMD algorithm. Some intrinsic mode function (IMF) components obtained from the VMD-SSA decomposition are grouped and reconstructed according to the interrelationship number selection criterion. Then, the reconstructed signal is further denoised by combining the strong noise-reduction ability of SVD to obtain a clean lidar return signal. To verify the effectiveness of the VMD-SSA-SVD method, the method is compared and analysed with wavelet packet decomposition, empirical modal decomposition (EMD), ensemble empirical modal decomposition (EEMD), and adaptive noise-complete ensemble empirical modal decomposition (CEEMD), and its noise-reduction effect is considerably improved over that of the other four methods. The method can eliminate the complex noise in the lidar return signal while retaining all the details of the signal. The signal is not distorted, the waveform is smoother, and far-field noise interference can be suppressed. The denoised signal is closer to the real signal with higher accuracy, which shows the feasibility and the practicality of the proposed method.

Laserfarm – A high-throughput workflow for generating geospatial data products of ecosystem structure from airborne laser scanning point clouds

Quantifying ecosystem structure is of key importance for ecology, conservation, restoration, and biodiversity monitoring because the diversity, geographic distribution and abundance of animals, plants and other organisms is tightly linked to the physical structure of vegetation and associated microclimates. Light Detection And Ranging (LiDAR) — an active remote sensing technique — can provide detailed and high resolution information on ecosystem structure because the laser pulse emitted from the sensor and its subsequent return signal from the vegetation (leaves, branches, stems) delivers three-dimensional point clouds from which metrics of vegetation structure (e.g. ecosystem height, cover, and structural complexity) can be derived. However, processing 3D LiDAR point clouds into geospatial data products of ecosystem structure remains challenging across broad spatial extents due to the large volume of national or regional point cloud datasets (typically multiple terabytes consisting of hundreds of billions of points). Here, we present a high-throughput workflow called ‘Laserfarm’ enabling the efficient, scalable and distributed processing of multi-terabyte LiDAR point clouds from national and regional airborne laser scanning (ALS) surveys into geospatial data products of ecosystem structure. Laserfarm is a free and open-source, end-to-end workflow which contains modular pipelines for the re-tiling, normalization, feature extraction and rasterization of point cloud information from ALS and other LiDAR surveys. The workflow is designed with horizontal scalability and can be deployed with distributed computing on different infrastructures, e.g. a cluster of virtual machines. We demonstrate the Laserfarm workflow by processing a country-wide multi-terabyte ALS dataset of the Netherlands (covering ∼34,000 km2 with ∼700 billion points and ∼ 16 TB uncompressed LiDAR point clouds) into 25 raster layers at 10 m resolution capturing ecosystem height, cover and structural complexity at a national extent. The Laserfarm workflow, implemented in Python and available as Jupyter Notebooks, is applicable to other LiDAR datasets and enables users to execute automated pipelines for generating consistent and reproducible geospatial data products of ecosystems structure from massive amounts of LiDAR point clouds on distributed computing infrastructures, including cloud computing environments. We provide information on workflow performance (including total CPU times, total wall-time estimates and average CPU times for single files and LiDAR metrics) and discuss how the Laserfarm workflow can be scaled to other LiDAR datasets and computing environments, including remote cloud infrastructures. The Laserfarm workflow allows a broad user community to process massive amounts of LiDAR point clouds for mapping vegetation structure, e.g. for applications in ecology, biodiversity monitoring and ecosystem restoration.

355-nm direct-detection Doppler wind lidar for vertical atmospheric motion measurement.

A compact and simple 355-nm direct-detection Doppler wind lidar (DDDWL) was developed to measure the line-of-sight (LOS) wind speed of the background atmosphere from atmospheric molecule return signals with and without aerosols and clouds. A receiver design with a Fabry-Perot etalon interferometer (FPEI) without an inside deposited step coating or fiber coupling is considered for the DDDWL using the double-edge technique. The receiver with the double-edge technique uses a FPEI and wedge prism to form a double-edge filter. The development of the double-edge filter in this combination is, to the best of our knowledge, an improvement at 355-nm wavelength. Considerations for the DDDWL receiver with a FPEI revealed that a full-angle light beam divergence into the FPEI and a working FPEI aperture are significant factors for the receiver design. Preliminary experimental evaluation demonstrated that the DDDWL had the potential of LOS wind speed measurements with a random error of less than 1 m/s when the signal-to-noise ratio was approximately 300. The DDDWL-measured vertical LOS wind speed profile was consistent with that of a 2-µm coherent Doppler wind lidar within the measurement error range. The preliminary experimental LOS wind measurement results demonstrated the capability of the DDDWL to measure low LOS wind speeds.

Axion electrodynamics: Energy–momentum tensor and possibilities for experimental tests

Axion electrodynamics is based upon the Lagrangian of the electromagnetic (EM) field plus its interaction with the axions, and is accordingly a physically open system. It means that the four-divergence of the EM energy–momentum tensor is different from zero, implying in turn that the total EM energy and momentum (when integrated over all space) do not constitute a four-vector. The EM force is in principle accessible to experimental detection, just analogous to what is the case in ordinary electrodynamics. In the first half of this paper the energy–momentum aspects of axion electrodynamics are worked out in general, when the surroundings are allowed to be a medium with constant permittivity and permeability. In the second half, two examples are discussed. The first is a static situation, where a block of uniform material containing axions is exposed to external strong electric and magnetic fields. Assuming the axion amplitude [Formula: see text] (i.e. its density) to increase linearly in one direction, we calculate the axion-generated forces. As a second example, we consider axions varying not with position but instead harmonically with time; this is the constellation usually assumed in astrophysics. Assuming a Gaussian profile for the EM wave emitted from the Earth towards an axion cloud in outer space, we make a calculation of the ‘axion echo’, the return signal.

Novel Inversion Algorithm for the Atmospheric Aerosol Extinction Coefficient Based on an Improved Genetic Algorithm

As an important atmospheric component, aerosols play a very important role in the radiation budget balance of the earth–atmosphere system. To study the optical characteristics of aerosols, it is necessary to use an inversion algorithm to process the lidar return signal to obtain both the aerosol extinction coefficient and the backscattering coefficient. However, the lidar return power equation is ill-conditioned and contains two unknown parameters, meaning that traditional inversion algorithms must be solved by adopting certain assumptions (e.g., a uniform atmosphere and the lidar ratio), which to a certain extent can seriously affect the inversion accuracy. Here, to improve the accuracy of the aerosol extinction coefficient inversion, an inversion method based on an improved genetic algorithm is proposed. Using the U.S. Standard Atmosphere model and the return power equation, the aerosol extinction coefficient and the backscattering coefficient are independent variables that randomly provide initial values to simulate the theoretical lidar power. Then, the genetic algorithm is used to approximate the theoretical lidar power to the measured lidar return power with height; when the two are infinitely close, the values of the corresponding two independent variables (i.e., the extinction and backscattering coefficients) are inverted. Experiments performed to compare the different effects between a simple genetic algorithm and the improved genetic algorithm showed the proposed method capable of inverting the aerosol extinction coefficient without reliance on traditional inversion methods, representing a novel approach to the inversion of the aerosol extinction coefficient and the backscattering coefficient.