Sensor Payload Research Articles

Martian Infrasound: Numerical Modeling and Analysis of InSight's Data

AbstractAcoustic waves in planetary atmospheres couple into the solid surface, producing ground displacements that can be measured using seismometers. On 26 November 2018, the InSight mission successfully landed on Mars. Its objectives include studying Mars' interior using the seismometer SEIS (Seismic Experiment for Interior Structures) and the atmosphere through the weather station APSS (Auxiliary Payload Sensor Suite). Because InSight is the first mission capable of studying infrasound on Mars, we investigate the signature of infrasound both in terms of air pressure and ground velocities. Using numerical simulations, we characterize (1) the acoustic propagation pattern in Martian dusk and (2) the mechanical atmosphere‐to‐ground coupling under acoustic waves. Then, using SEIS data, we demonstrate that two low‐frequency monotone events (S0133a and S0189a) are in fact infrasound trapped in the atmospheric nocturnal surface waveguide. We base our demonstration on the following facts. (1) Seismic signals rarely produce, at a given station, a single frequency varying from one event to the other. (2) No clear seismic phases have been identified for such events. (3) The observed SEIS signals present the characteristics expected for trapped infrasound observed through their compliance effects (specific frequency response, more energy on the vertical component, ±90° phase shift between vertical and horizontal components, and no detection on pressure sensor at these low amplitude levels). Our simulations of the nocturnal waveguide's response are however subject to uncertainties because (1) it relies on the sol‐to‐sol variability of the atmosphere, and (2) subsurface properties are not properly known at this time.

A Tethered Air Blimp (TAB) for observing the microclimate over a complex terrain

Abstract. This study presents the first environmental monitoring field campaign of a newly developed Tethered Air Blimp (TAB) system to investigate the microclimate over a complex terrain. The use of a tethered balloon in complex terrains such as mines and tailings ponds is novel and the focus of the present study. The TAB system was fully developed and launched at a mining facility in northern Canada in May 2018. This study describes the key design features, the sensor payload on board, calibration, and the observations made by the TAB system. The system measured meteorological conditions including components of wind velocity vector, temperature, relative humidity, and pressure over the first few tens of metres of the atmospheric boundary layer. The measurements were made at two primary locations in the facility: (i) near a tailings pond and (ii) in a mine pit. TAB measured the dynamics of the atmosphere at different diurnal times (e.g. day versus night) and locations (near a tailings pond versus inside the mine). Such dynamics include mean and turbulence statistics pertaining to flow momentum and energy, and they are crucial in the understanding of emission fluxes from the facility in future studies. In addition, TAB can provide boundary conditions and validation datasets to support mesoscale dispersion modelling or computational fluid dynamics simulations for various transport models.

Spatiotemporal Camera-LiDAR Calibration: A Targetless and Structureless Approach

The demand for multimodal sensing systems for robotics is growing due to the increase in robustness, reliability and accuracy offered by these systems. These systems also need to be spatially and temporally co-registered to be effective. In this letter, we propose a targetless and structureless spatiotemporal camera-LiDAR calibration method. Our method combines a closed-form solution with a modified structureless bundle adjustment where the coarse-to-fine approach does not require an initial guess on the spatiotemporal parameters. Also, as 3D features (structure) are calculated from triangulation only, there is no need to have a calibration target or to match 2D features with the 3D point cloud which provides flexibility in the calibration process and sensor configuration. We demonstrate the accuracy and robustness of the proposed method through both simulation and real data experiments using multiple sensor payload configurations mounted to hand-held, aerial and legged robot systems. Also, qualitative results are given in the form of a colorized point cloud visualization.

OpenSHC: A Versatile Multilegged Robot Controller

Multilegged robots have the ability to perform stable locomotion on relatively rough terrain. However, the complexity of legged robots over wheeled or tracked robots make them difficult to control. This paper presents OpenSHC (Open-source Syropod High-level Controller), a versatile high-level controller capable of generating gaits and poses for quasi-static multilegged robots, both simulated and with real hardware implementations. With full Robot Operating System (ROS) integration, the controller can be quickly deployed on robots with different actuators and sensor payloads. The flexibility of OpenSHC is demonstrated on the 30 degrees of freedom hexapod Bullet, analysing the energetic performance of various leg configurations, kinematic arrangements and gaits over different locomotion speeds. With OpenSHC being easily configured to different physical and locomotion specifications, a hardware-based parameter space search for optimal locomotion parameters is conducted. The experimental evaluation shows that the mammalian configuration offers lower power consumption across a range of step frequencies; with the insectoid configuration providing performance advantages at higher body velocities and increased stability at low step frequencies. OpenSHC is open-source and able to be configured for various number of joints and legs.

Proof of concept apparatus for the design of a simple, low cost, mobile e-nose for real-time victim localization (human presence) based on indoor air quality monitoring sensors

Indoor air quality monitoring sensor devices that are simple to operate, low cost and readily available were tested in an apparatus capable of preparing, storing, and manipulating air samples. Suitably prepared air samples were captured and measured with the apparatus emulating the conditions anticipated in the target application, i.e the detection of humans in confined and poorly ventilated spaces during Urban Search and Rescue Operations. The apparatus and the testing methodology, that were designed in order to evaluate the suitability of the selected sensors for implementing an electronic nose (e-nose) for human detection, are presented. Currently an e-nose system that is under development, adopted the architecture finalized in the presented work, and is intended to be used during the Assessment, Search and Rescue (ASR) stage 4 of a USaR operation as part of the sensor payload of a remotely controlled robot that enters the rubble of collapsed structures searching for trapped victims. The planned prototype will be tested in near realistic conditions.

EarthScope-Oceans: An array of floating MERMAID instruments for earthquake seismology

Mapping the Earth's uncharted interior through global seismic tomography is dependent on increasing the number of seismic stations in the oceans. We have developed a low-cost, autonomously floating hydrophone to capture earthquake signals suitable for the study of the interior of the Earth and the tectonically and magmatically active underwater realm, while it maintains its potential to be an environmental monitoring device. MERMAID is a freely drifting diver that combines (1) a hydrophone, (2) GPS, (3) an on-board digitizing and processing unit that uses wavelet detection and discrimination algorithms, and (4) an iridium unit for near real-time data transfer with two-way communication. The instrument, 50 kg in air, submersible to 3000 m water depth, with a projected lifetime of up to 5 years, is commercially available from OSEAN SAS. Some 60 units will have been deployed in the Pacific Ocean by the Fall of 2019. With up to 7 kg of sensor payload, additional configurable sensors today include a Sea-Bird SBE 41 CTD, and, in the future, a suite of other instruments with utility in bioacoustics, environmental monitoring, meteorology, bathymetric determination, and chemical and physical oceanography. We report on the performance of our instruments as regards teleseismic event recovery, and on the development of a new method for extracting high-resolution travel times from the first ~1500 seismograms reported live from the Pacific Ocean.

Dynamics and Control of a Collaborative and Separating Descent of Samara Autorotating Wings

To deliver lightweight sensor payloads to disaster-struck areas by means of an aerial deployment, a novel bio-inspired method capitalizing on autorotation to slow down vertical descent rate is proposed. This concept is illustrated using the samara autorotating wing (SAW) platform, which features a unique collaborative mode where multiple individual units are attached mechanically together to form a collective rotor hub for increased controllability. This rotor is designed with a simple de-centralized separation mechanism to detach into singular units during flight upon command, catering to different mission profiles. The dynamic models for singular state and collaborative rotor hub state were developed, and free-flight simulations were conducted in different modes including the separation stage and control performance for both states was analyzed. Experiments were set up for increased motion-capture region and free-flight drop tests and separation flights were carried out to verify the simulations. Finally, using a multi-rotor as an aerial launch platform, control performance for the single-winged state was evaluated in real-world conditions.

Describing seasonal differences in tree crown delineation using multispectral UAS data and structure from motion

ABSTRACTUnmanned Aerial Systems (UAS) have emerged as a platform capable of providing valuable data on vegetation structure, health, and productivity. The platform provides maximum temporal flexibility in data collection and customizability of spatial footprints which is important for mapping and monitoring vegetation conditions especially for high spectrally and structurally heterogeneous landscapes. In this letter, we investigate the potential improvement in structural information when using sensor payloads that include infrared bands (730–810 nm) in addition to the typical visible bands of many UAS sensor payloads. Specifically, we use derived point clouds and imagery collected from UAS-mounted sensors at a test site in Louisville, Kentucky, USA to assess whether multispectral sensors improve estimates of vegetation structure for plant greenness (leaf-on) and senescence (leaf-off) periods. Results indicate that including detailed multispectral reflectance information beyond the visible portion of the electromagnetic spectrum aids in estimating structural characteristics of woody vegetation, regardless of season. While both leaf-on and leaf-off periods result in reasonable crown height estimates, leaf-on conditions also improve radial estimates, likely due to continuous canopy surfaces. These findings advance research for remote sensing analyses assessing structural composition in heterogeneous landscapes where varying levels of vegetation structure have implications on land use and land function.

Space Technology Applications for Maritime Intelligence, Surveillance, and Reconnaissance

ABSTRACTOuter space, as the ultimate high ground, offers potential for contributing towards maritime domain awareness, which is dependent on Intelligence, Surveillance, and Reconnaissance (ISR). This research discusses several utilizations and limitations of space technologies in the realm of maritime ISR through use of electronic intelligence, and electro-optical and radar imagery payload sensors. Technological and financial options for nascent and smaller space powers through dual-purpose commercial and civilian space technologies towards sea surveillance are elaborated as well. Finally, from an operational perspective of ISR, the methodology of frame-by-frame mosaicking of satellite images utilizing commercial remote sensing satellites towards space-based maritime ISR is explained using hypothetical scenarios.

A UAV-Based Sensor System for Measuring Land Surface Albedo: Tested over a Boreal Peatland Ecosystem

A multiple sensor payload for a multi-rotor based UAV platform was developed and tested for measuring land surface albedo and spectral measurements at user-defined spatial, temporal, and spectral resolutions. The system includes a Matrice 600 UAV with an RGB camera and a set of four downward pointing radiation sensors including a pyranometer, quantum sensor, and VIS and NIR spectrometers, measuring surface reflected radiation. A companion ground unit consisting of a second set of identical sensors simultaneously measure downwelling radiation. The reflected and downwelling radiation measured by the four sensors are used for calculating albedo for the total shortwave broadband, visible band and any narrowband at a 1.5 nm spectral resolution within the range of 350–1100 nm. The UAV-derived albedo was compared with those derived from Landsat 8 and Sentinel-2 satellite observations. Results show the agreement between total shortwave albedo from UAV pyranometer and Landsat 8 (R2 = 0.73) and Sentinel-2 (R2 = 0.68). Further, total shortwave albedo was estimated from spectral measurements and compared with the satellite-derived albedo. This UAV-based sensor system promises to provide high-resolution multi-sensors data acquisition. It also provides maximal flexibility for data collection at low cost with minimal atmosphere influence, minimal site disturbance, flexibility in measurement planning, and ease of access to study sites (e.g., wetlands) in contrast with traditional data collection methods.

NU-Spidercam: A large-scale, cable-driven, integrated sensing and robotic system for advanced phenotyping, remote sensing, and agronomic research

Field-based high throughput plant phenotyping has recently gained increased interest in the efforts to bridge the genotyping and phenotyping gap and accelerate plant breeding for crop improvement. In this paper, we introduce a large-scale, integrated robotic cable-driven sensing system developed at University of Nebraska for field phenotyping research. It is constructed to collect data from a 0.4 ha field. The system has a sensor payload of 30 kg and offers the flexibility to integrate user defined sensing modules. Currently it integrates a four-band multispectral camera, a thermal infrared camera, a 3D scanning LiDAR, and a portable visible near-infrared spectrometer for plant measurements. Software is designed and developed for instrument control, task planning, and motion control, which enables precise and flexible phenotypic data collection at the plot level. The system also includes a variable-rate subsurface drip irrigation to control water application rates, and an automated weather station to log environmental variables. The system has been in operation for the 2017 and 2018 growing seasons. We demonstrate that the system is reliable and robust, and that fully automated data collection is feasible. Sensor and image data are of high quality in comparison to the ground truth measurements, and capture various aspects of plant traits such as height, ground cover and spectral reflectance. We present two novel datasets enabled by the system, including a plot-level thermal infrared image time-series during a day, and the signal of solar induced chlorophyll fluorescence from canopy reflectance. It is anticipated that the availability of this automated phenotyping system will benefit research in field phenotyping, remote sensing, agronomy, and related disciplines.

Dynamics of Outgassing and Plume Transport Revealed by Proximal Unmanned Aerial System (UAS) Measurements at Volcán Villarrica, Chile

AbstractVolcanic gas emissions are intimately linked to the dynamics of magma ascent and outgassing and, on geological time scales, constitute an important source of volatiles to the Earth's atmosphere. Measurements of gas composition and flux are therefore critical to both volcano monitoring and to determining the contribution of volcanoes to global geochemical cycles. However, significant gaps remain in our global inventories of volcanic emissions, (particularly for CO2, which requires proximal sampling of a concentrated plume) for those volcanoes where the near‐vent region is hazardous or inaccessible. Unmanned Aerial Systems (UAS) provide a robust and effective solution to proximal sampling of dense volcanic plumes in extreme volcanic environments. Here we present gas compositional data acquired using a gas sensor payload aboard a UAS flown at Volcán Villarrica, Chile. We compare UAS‐derived gas time series to simultaneous crater rim multi‐GAS data and UV camera imagery to investigate early plume evolution. SO2 concentrations measured in the young proximal plume exhibit periodic variations that are well correlated with the concentrations of other species. By combining molar gas ratios (CO2/SO2 = 1.48–1.68, H2O/SO2 = 67–75, and H2O/CO2 = 45–51) with the SO2 flux (142 ± 17 t/day) from UV camera images, we derive CO2 and H2O fluxes of ~150 t/day and ~2,850 t/day, respectively. We observe good agreement between time‐averaged molar gas ratios obtained from simultaneous UAS‐ and ground‐based multi‐GAS acquisitions. However, the UAS measurements made in the young, less diluted plume reveal additional short‐term periodic structure that reflects active degassing through discrete, audible gas exhalations.

Analyze Angle of the Camera Payload LSU-02 in Mission of Aerial Photo

In carrying out its mission, LAPAN Surveillance UAV version 2 (LSU-02) was equipped with a camera payload sensor mounted on a gimbal system. When taking upright aerial photos according to photogrammetric requirements, the axis of the aerial camera must be aligned with the direction of gravity with a slope tolerance less than 3 degrees (<3°), so that the shooting results meet the map to the desired standard. The camera payload was equipped with a 3-axis gimbal system which pitch and roll directions installed by the gyro sensor to measure the camera's tilt angle. Gimbal camera payload with dimensions (160×170×155) mm are designed to be installed on a casing (190×190×180) mm according to the available space in the LSU-02 payload space, which was the length x width x height (190×190×180) mm. Testing was done by flying LSU-02 on Rumpin and Pamengpeuk runway. From the test results, it was obtained the deviation of roll and pitch angle less than 3degree, which the gimbal angle oscillation when the payload camera shooting was only ± 1 degree with the respon time until it reaches a stable condition of approximately 35 to 55 seconds, and the offset value for roll and pitch approximately -1 degree, which it has met the standard for making aerial photo maps according to photogrammetric requirements.

InSight Auxiliary Payload Sensor Suite (APSS)

NASA’s InSight mission to Mars will measure seismic signals to determine the planet’s interior structure. These highly sensitive seismometers are susceptible to corruption of their measurements by environmental changes. Magnetic fields, atmosphere pressure changes, and local winds can all induce apparent changes in the seismic records that are not due to propagating ground motions. Thus, InSight carries a set of sensors called the Auxiliary Payload Sensor Suite (APSS) which includes a magnetometer, an atmospheric pressure sensor, and a pair of wind and air temperature sensors. In the case of the magnetometer, knowledge of the amplitude of the fluctuating magnetic field at the InSight lander will allow the separation of seismic signals from potentially interfering magnetic signals of either natural or spacecraft origin. To acquire such data, a triaxial fluxgate magnetometer was installed on the deck of the lander to obtain magnetic records at the same cadence as the seismometer. Similarly, a highly sensitive pressure sensor is carried by InSight to enable the removal of local ground-surface tilts due to advecting pressure perturbations. Finally, the local winds (speed and direction) and air temperature are estimated using a hot-film wind sensor with heritage from REMS on the Curiosity rover. When winds are too high, seismic signals can be ignored or discounted. Herein we describe the APSS sensor suite, the test programs for its components, and the possible additional science investigations it enables.

Atmospheric Science with InSight

In November 2018, for the first time a dedicated geophysical station, the InSight lander, will be deployed on the surface of Mars. Along with the two main geophysical packages, the Seismic Experiment for Interior Structure (SEIS) and the Heat-Flow and Physical Properties Package (HP3), the InSight lander holds a highly sensitive pressure sensor (PS) and the Temperature and Winds for InSight (TWINS) instrument, both of which (along with the InSight FluxGate (IFG) Magnetometer) form the Auxiliary Sensor Payload Suite (APSS). Associated with the RADiometer (RAD) instrument which will measure the surface brightness temperature, and the Instrument Deployment Camera (IDC) which will be used to quantify atmospheric opacity, this will make InSight capable to act as a meteorological station at the surface of Mars. While probing the internal structure of Mars is the primary scientific goal of the mission, atmospheric science remains a key science objective for InSight. InSight has the potential to provide a more continuous and higher-frequency record of pressure, air temperature and winds at the surface of Mars than previous in situ missions. In the paper, key results from multiscale meteorological modeling, from Global Climate Models to Large-Eddy Simulations, are described as a reference for future studies based on the InSight measurements during operations. We summarize the capabilities of InSight for atmospheric observations, from profiling during Entry, Descent and Landing to surface measurements (pressure, temperature, winds, angular momentum), and the plans for how InSight’s sensors will be used during operations, as well as possible synergies with orbital observations. In a dedicated section, we describe the seismic impact of atmospheric phenomena (from the point of view of both “noise” to be decorrelated from the seismic signal and “signal” to provide information on atmospheric processes). We discuss in this framework Planetary Boundary Layer turbulence, with a focus on convective vortices and dust devils, gravity waves (with idealized modeling), and large-scale circulations. Our paper also presents possible new, exploratory, studies with the InSight instrumentation: surface layer scaling and exploration of the Monin-Obukhov model, aeolian surface changes and saltation / lifing studies, and monitoring of secular pressure changes. The InSight mission will be instrumental in broadening the knowledge of the Martian atmosphere, with a unique set of measurements from the surface of Mars.

Colourising Point Clouds Using Independent Cameras

We investigate the problem of colourising a point cloud using an arbitrary mobile mapping device and an independent camera. The loose coupling of sensors creates a number of challenges related to timing, point visibility, and colour determination. We address each of these problems and demonstrate our resulting algorithm on data captured using sensor payloads mounted to hand-held, aerial, and ground systems, illustrating the “plug-and-play” portability of the method.

Isolation of Seismic Signal from InSight/SEIS-SP Microseismometer Measurements

The InSight mission is due to launch in May 2018, carrying a payload of novel instruments designed and tested to probe the interior of Mars whilst deployed directly on the Martian regolith and partially isolated from the Martian environment by the Wind and Thermal Shield. Central to this payload is the seismometry package SEIS consisting of two seismometers, which is supported by a suite of environmental/meteorological sensors (Temperature and Wind Sensor for InSight TWINS; and Auxiliary Payload Sensor Suite APSS). In this work, an optimal estimations inversion scheme which aims to decorrelate the short-period seismometer (SEIS-SP) signal due to seismic activity alone from the environmental signal and random noise is detailed, and tested on both simulated and Viking data. This scheme also applies a module to identify measurements contaminated by Single Event Phenomena (SEP). This scheme will be deployed as the pre-processing pipeline for all SEIS-SP data prior to release to the scientific community for analysis.

Sensing water properties at precise depths from the air

AbstractWater properties are critical to our understanding and managing of freshwater systems that change rapidly with depth. This work presents an unmanned aerial vehicle (UAV) ‐based method of keeping a submerged, cable‐suspended sensor payload at a precise depth, with 95% of sensor readings within ±8.4 cm of the target depth. We use a depth altimeter attached at the terminus of a 3.5 m semirigid cable as the sole input to a depth controller actuated by the UAV's motors. First, we simulate the UAV‐cable‐payload system with disturbances of wind, water, signal delay, and GPS drift and then use parameters discovered during simulation to guide implementation. We characterize the depth altimeter during translation and find that 95% of the readings are within ±7 mm of ground truth, with a steady‐state error of ±3 mm. In field experiments, we compare the depth precision of our new method to previous methods that used the UAV's altitude as a proxy for submerged sensor depth, specifically 1) only using the UAV's air pressure altimeter; and 2) fusing UAV‐mounted ultrasonic sensors with the air pressure altimeter. Our new method reduces the standard deviation of depth readings from 16.1 to 4.2 cm in winds up to 8.0 ms−1. We show the step response of the depth‐altimeter method when transitioning between target depths. Finally, we explore a longer, 8.0 m cable and show that our depth controller still outperforms air altimeter and ultrasonic methods and allows scientists to increase the spatiotemporal resolution of water property datasets.

Measuring wind with Small Unmanned Aircraft Systems

Small Unmanned Aircraft Systems (SUAS) are an emerging technology that is suitable for multitude of applications requiring small sensor payloads including airborne wind measurement. This work discusses the considerations and limitations of different SUAS configurations, in particular Multi-rotor UAS (MUAS), and their capabilities when operating within the Atmospheric Boundary Layer (ABL). Several methods for measuring fluctuating flows from SUAS are discussed, and preliminary results from a quadrotor-mounted Multi-Hole Pressure Probe (MHPP) “flying anemometer” platform are presented. Flights at a range of altitudes demonstrated that in-situ measurements of both mean wind velocity and turbulence intensity from hovering airborne platform are feasible. This indicates that MUAS can be used as flexible wind sensing platforms with good high spatial resolution. Suggestions for how future SUAS technological and operation developments may further improve wind engineering applications are also discussed.

New Setup of the UAS ALADINA for Measuring Boundary Layer Properties, Atmospheric Particles and Solar Radiation

The unmanned research aircraft ALADINA (Application of Light-weight Aircraft for Detecting in situ Aerosols) has been established as an important tool for boundary layer research. For simplified integration of additional sensor payload, a flexible and reliable data acquisition system was developed at the Institute of Flight Guidance, Technische Universität (TU) Braunschweig. The instrumentation consists of sensors for temperature, humidity, three-dimensional wind vector, position, black carbon, irradiance and atmospheric particles in the diameter range of ultra-fine particles up to the accumulation mode. The modular concept allows for straightforward integration and exchange of sensors. So far, more than 200 measurement flights have been performed with the robustly-engineered system ALADINA at different locations. The obtained datasets are unique in the field of atmospheric boundary layer research. In this study, a new data processing method for deriving parameters with fast resolution and to provide reliable accuracies is presented. Based on tests in the field and in the laboratory, the limitations and verifiability of integrated sensors are discussed.