The geoPebble System: Design and Implementation of a Wireless Sensor Network of GPS-Enabled Seismic Sensors for the Study of Glaciers and Ice Sheets

The geoPebble system is a network of wirelessly interconnected seismic and GPS sensor nodes with geophysical sensing capabilities for the study of ice sheets in Antarctica and Greenland, as well as mountain glaciers. We describe our design methodology, which has enabled us to develop these state-of-the art units using commercial-off-the-shelf hardware combined with custom-designed hardware and software. Each geoPebble node is a self-contained, wirelessly connected sensor for collecting seismic activity and position information. Each node is built around a three-component seismic recorder, which includes an amplifier, filter, and 24-bit analog-to-digital converter that can sample incoming seismic signals up to 10 kHz. The timing for each node is available from GPS measurements and a local precision oscillator that is conditioned by the GPS timing pulses. In addition, we record the carrier-phase measurement of the L1 GPS signal in order to determine location at sub-decimeter accuracy (relative to other geoPebble nodes within a radius of a few kilometers). Each geoPebble includes 32 GB of solid-state storage, wireless communications capability to a central supervisory unit, and auxiliary measurements capability (including tilt from accelerometers, absolute orientation from magnetometers, and temperature). The geoPebble system has been successfully validated in the field in Antarctica and Greenland.

Reconfigurable Framework for Resilient Semantic Segmentation for Space Applications

Deep learning (DL) presents new opportunities for enabling spacecraft autonomy, onboard analysis, and intelligent applications for space missions. However, DL applications are computationally intensive and often infeasible to deploy on radiation-hardened (rad-hard) processors, which traditionally harness a fraction of the computational capability of their commercial-off-the-shelf counterparts. Commercial FPGAs and system-on-chips present numerous architectural advantages and provide the computation capabilities to enable onboard DL applications; however, these devices are highly susceptible to radiation-induced single-event effects (SEEs) that can degrade the dependability of DL applications. In this article, we propose Reconfigurable ConvNet (RECON), a reconfigurable acceleration framework for dependable, high-performance semantic segmentation for space applications. In RECON, we propose both selective and adaptive approaches to enable efficient SEE mitigation. In our selective approach, control-flow parts are selectively protected by triple-modular redundancy to minimize SEE-induced hangs, and in our adaptive approach, partial reconfiguration is used to adapt the mitigation of dataflow parts in response to a dynamic radiation environment. Combined, both approaches enable RECON to maximize system performability subject to mission availability constraints. We perform fault injection and neutron irradiation to observe the susceptibility of RECON and use dependability modeling to evaluate RECON in various orbital case studies to demonstrate a 1.5–3.0× performability improvement in both performance and energy efficiency compared to static approaches.

CycleGuard

Every year 41,000 cyclists die in road traffic-related incidents worldwide [47]. One of the most startling and infuriating conflicts that cyclists experience is the so-called "right hook". It refers to a vehicle striking a cyclist heading in the same direction by turning right into the cyclist. To prevent such a crash, this work presents CycleGuard, an acoustic-based collision detection system using smartphones. It is composed of a cheap commercial off-the-shelf (COTS) portable speaker that emits imperceptible high-frequency acoustic signals and a smartphone for reflected signal reception and analysis. Since received acoustic signals bear rich information of their reflecting objects, CycleGuard applies advanced acoustic ranging techniques to extract those information for traffic analysis. Cyclists are alerted if any pending right hook crashes are detected. Real-time alerts ensure that cyclists have sufficient time to react, apply brakes, and eventually avoid the hazard. To validate the efficacy of CycleGuard, we implement a proof-of-concept prototype and carry out extensive in-field experiments under a broad spectrum of settings. Results show that CycleGuard achieves up to 95% accuracy in preventing right hook crashes and is robust to various scenarios. It is also energy-friendly to run on battery-powered smartphones.

Development of an in situ Acoustic Anemometer to Measure Wind in the Stratosphere for SENSOR

The Stratospheric Environmental respoNses to Solar stORms (SENSOR) campaign investigates the influence of solar storms on the stratosphere. This campaign employs a long-duration zero-pressure balloon as a platform to carry multiple types of payloads during a series of flight experiments in the mid-latitude stratosphere from 2019 to 2022. This article describes the development and testing of an acoustic anemometer for obtaining in situ wind measurements along the balloon trajectory. Developing this anemometer was necessary, as there is no existing commercial off-the-shelf product, to the authors’ knowledge, capable of obtaining in situ wind measurements on a high-altitude balloon or other similar floating platform in the stratosphere. The anemometer is also equipped with temperature, pressure, and humidity sensors from a Temperature-Pressure-Humidity measurement module, inherited from a radiosonde developed for sounding balloons. The acoustic anemometer and other sensors were used in a flight experiment of the SENSOR campaign that took place in the Da chaidan District (95.37° E, 37.74° N) on 4 September 2019. Three-dimensional wind speed observations, which were obtained during level flight at an altitude of around 25 km, are presented. A preliminary analysis of the measurements yielded by the anemometer are also discussed. In addition to wind speed measurements, temperature, pressure, and relative humidity measurements during ascent are compared to observations from a nearby radiosonde launched four hours earlier. The problems experienced by the acoustic anemometer during the 2019 experiment show that the acoustic anemometer must be improved for future experiments in the SENSOR campaign.

A 10 kHz to 6 GHz Low-Cost Vector Network Analyzer

This publication introduces a low-cost vector network analyzer with very large frequency range made of commercial off-the-shelf components. It utilizes two identical receivers and two directional bridges to allow for two fully bidirectional measurement ports. The design surpasses the performance of competing low-cost network analyzers in regards of dynamic range, frequency span and calibration capability.

End-to-End Sequential Indoor Localization Using Smartphone Inertial Sensors and WiFi

This paper addresses sequential indoor localization using WiFi and Inertial Measurement Unit (IMU) modules commonly found in commercial off-the-shelf smartphones. Specifically, we developed an end-to-end neural network-based localization system integrating WiFi received signal strength indicator (RSSI) and IMU data without external data fusion models. The developed system leverages the advantages of WiFi and IMU modules to locate finer-level sequential positions of a user at 150 Hz sampling rate. Additionally, to demonstrate the efficacy of the proposed approach, we created the IMUWiFine dataset comprising IMU and WiFi RSSI readings sequentially collected at fine-level reference points. The dataset contains 120 trajectories covering an aggregate distance of over 14 kilometers. We conducted extensive experiments using deep learning models and achieved a mean error distance of 1.1 meters on an unseen evaluation set, which makes our approach suitable for many practical applications requiring meter-level accuracy. To enable experiment and result reproducibility, we made the developed localization system and IMUWiFine dataset publicly available in our GitHub repository.<br>

End-to-End Sequential Indoor Localization Using Smartphone Inertial Sensors and WiFi

This paper addresses sequential indoor localization using WiFi and Inertial Measurement Unit (IMU) modules commonly found in commercial off-the-shelf smartphones. Specifically, we developed an end-to-end neural network-based localization system integrating WiFi received signal strength indicator (RSSI) and IMU data without external data fusion models. The developed system leverages the advantages of WiFi and IMU modules to locate finer-level sequential positions of a user at 150 Hz sampling rate. Additionally, to demonstrate the efficacy of the proposed approach, we created the IMUWiFine dataset comprising IMU and WiFi RSSI readings sequentially collected at fine-level reference points. The dataset contains 120 trajectories covering an aggregate distance of over 14 kilometers. We conducted extensive experiments using deep learning models and achieved a mean error distance of 1.1 meters on an unseen evaluation set, which makes our approach suitable for many practical applications requiring meter-level accuracy. To enable experiment and result reproducibility, we made the developed localization system and IMUWiFine dataset publicly available in our GitHub repository.<br>

Improving winter traction for vehicles in northern operations

As part of the campaign to increase readiness in northern regions, a near commercial off-the-shelf (COTS) solution was identified for the High Mobility Multipurpose Wheeled Vehicle (HMMWV); and used to assess the suitability of commercially available winter tires for operational deployment. Initial performance evaluations conducted during the winters of 2020 and 2021 demonstrated and quantified significant improvements to traction and handling on a variety of winter surfaces. User feedback from United States Army Alaska (USARAK) Soldiers confirmed these results in an operational environment. Results of this study provide new winter tire specifications for the Army and justify the procurement of a HMMWV winter tire for improved safety and capability for US Soldier and vehicle fleet needs. The data and Soldier evaluations support attaining a National Stock Number (NSN) and provide data to develop models of winter vehicle performance that include the impact of winter tires and chains. This work also paves the way for future development and procurement of winter tires for vehicles where COTS solutions are unavailable. The motivation is to provide Soldiers with state-of-the-art winter tires to increase safety, capability, and operational compatibility with North Atlantic Treaty Organization (NATO) partners in the European Theater of Operations, and mobility superiority in all environments.

Soft and Hard Iron Compensation for the Compasses of an Operational Towed Hydrophone Array without Sensor Motion by a Helmholtz Coil

Usually, towed hydrophone arrays are instrumented with a set of compasses. Data from these sensors are utilized while beamforming the acoustic signal for target bearing estimation. However, elements of the hydrophone array mounted in the neighborhood of a compass can affect the Earth’s magnetic field detection. The effects depend upon the materials and magnetic environment present in the vicinity of the platform hosting the compass. If the disturbances are constant in time, they can be compensated for by means of a magnetic calibration procedure. This process is commonly known as soft and hard iron compensation. In this paper, a solution is presented for carrying out the magnetic calibration of a COTS (Commercial Off the Shelf) digital compass without sensor motion. This approach is particularly suited in applications where a physical rotation of the platform that hosts the sensor is unfeasible. In our case, the platform consists in an assembled and operational towed hydrophone array. A standard calibration process relies on physical rotation of the platform and thus on the use of the geomagnetic field as a reference during the compensation. As a variation on this approach, we generate an artificial reference magnetic field to simulate the impractical physical rotation. We obtain this by using a tri-axial Helmholtz coil, which enables programmability of the reference magnetic field and assures the required field uniformity. In our work, the simulated geomagnetic field is characterized in terms of its uncertainty. The analysis indicates that our method and experimental set-up represent a suitably accurate approach for the soft and hard iron compensation of the compasses equipped in the hydrophone array under test.

In situ science on Phobos with the Raman spectrometer for MMX (RAX): preliminary design and feasibility of Raman measurements

Mineralogy is the key to understanding the origin of Phobos and its position in the evolution of the Solar System. In situ Raman spectroscopy on Phobos is an important tool to achieve the scientific objectives of the Martian Moons eXploration (MMX) mission, and maximize the scientific merit of the sample return by characterizing the mineral composition and heterogeneity of the surface of Phobos. Conducting in situ Raman spectroscopy in the harsh environment of Phobos requires a very sensitive, compact, lightweight, and robust instrument that can be carried by the compact MMX rover. In this context, the Raman spectrometer for MMX (i.e., RAX) is currently under development via international collaboration between teams from Japan, Germany, and Spain. To demonstrate the capability of a compact Raman system such as RAX, we built an instrument that reproduces the optical performance of the flight model using commercial off-the-shelf parts. Using this performance model, we measured mineral samples relevant to Phobos and Mars, such as anhydrous silicates, carbonates, and hydrous minerals. Our measurements indicate that such minerals can be accurately identified using a RAX-like Raman spectrometer. We demonstrated a spectral resolution of approximately 10 cm−1, high enough to resolve the strongest olivine Raman bands at ~ 820 and ~ 850 cm−1, with highly sensitive Raman peak measurements (e.g., signal-to-noise ratios up to 100). These results strongly suggest that the RAX instrument will be capable of determining the minerals expected on the surface of Phobos, adding valuable information to address the question of the moon’s origin, heterogeneity, and circum-Mars material transport. Graphical Abstract