Limited Telemetry Research Articles

Resilient Operation Planning for CubeSat Using Reinforcement Learning

This study proposes an autonomous operation procedure for a CubeSat by applying reinforcement learning based on resilient engineering. The CubeSat requires rapid judgment in every visible window based on a sufficient understanding of the health conditions of the satellite from limited telemetry data due to the limited communication performance and poor protection functions from the harsh environment. This study first performs a risk analysis by using System Theoretic Process Analysis (STPA) to evaluate the risk scenario of the Cube-Sat. In order to successfully operate the missions while avoiding the risk scenarios, reinforcement learning is applied to learn adequate behaviors according to the satellite situations such as the temperature and voltage of the installed battery, the sunlight and eclipse phase and the mission progress and plan. Through numerical examples, the validity of the proposed method is illustrated.

Abstract 150: Safety And Feasibility Of An ED-To-Outpatient Pathway For Transient Ischemic Attack Or Non-Disabling Stroke

Introduction: The evaluation and risk stratification of patients with TIA/non-disabling ischemic stroke (TIA/NDS) arriving to the Emergency Department (ED) incurs high-cost imaging and increases ED length of stay (EDLOS). We evaluated the safety and feasibility of an ED-to-Outpatient Pathway for TIA/NDS. Methods: In April 2020, we developed a risk stratification algorithm for TIA/NDS in the ED using features of the clincal presentation, limited blood tests, telemetry, and head-neck CT/CTA. Patients deemed low risk based on a “safety checklist” were discharged with plans for expedited outpatient testing as warranted (e.g., brain MRI, echocardiogram) followed by rapid outpatient follow-up. To assess safety/feasibility of this pathway, we analyzed data of the first 101 patients prospectively enrolled through October 2020. Results: Mean age 68 years (range, 33-99); 53% men; median NIHSS score 0 (range 0-3). Symptom duration was classified as <10 min (24%), 10-59 min (23%), >60 min (49%), unclear (4%). Deficits included isolated weakness (16%), isolated aphasia (15%), amaurosis fugax (6%), numbness/combined deficits/other (63%). Median ABCD2 score 3 (range 1-7). Outpatient follow-up included stroke clinic (82%), primary care (4%), not required or patient declined (6%), other hospital (1%); 7% were lost to follow-up; 43% had follow-up within 7 days. Imaging performed in the ED included CT/CTA only (39%), MRI/MRA only (27%), both (33%), or no imaging (1%). EDLOS was significantly less for patients when CT/CTA only was performed, as per pathway (12.8 versus 16.8 hours, p<0.05). The safety checklist was followed in 69% of patients. When the checklist was used properly, there were 0 recurrent strokes or TIAs within 90-days (versus 2 when not used correctly, p<0.05). Return rates to the ED were 8% with use of checklist and 6% without use (p=0.76). Conclusion: Our TIA/NDS pathway, implemented shortly after the outbreak of Covid-19 in the USA, significantly decreased EDLOS, and still allowed for TIA/NDS patients to be safely discharged from the ED. Acceptable risk stratification and safety is suggested by the low rates of recurrent events when the pathway was followed properly. More education is needed to ensure consistent and proper use of the pathway.

FPGA Design for On‐Board Measurement of Intermittency From In‐Situ Satellite Data

AbstractIntermittency is a fundamental property of space plasma dynamics, characterizing turbulent dynamical variables as well as passive scalars. Its qualitative and quantitative description from in‐situ data requires an accurate estimation of the probability density functions (PDFs) of fluctuations and their moments, particularly the flatness, a normalized fourth order moment of the PDF. Such a statistical description needs a sufficiently large number of samples for the computation to be meaningful. Due to inherent technological limitations (e.g., limited telemetry bandwidth) not all samples collected on‐board can be sent to the ground for further analysis. Therefore, a technology designed to process on‐board the data and to compute the flatness is useful to fully exploit the capabilities of scientific instruments installed on robotic platforms, including nanosatellites. We designed, built, and tested in laboratory such a technology based on Field Programable Gate Arrays (FPGA). The building principle is the classical estimation of PDFs and their moments, based on normalized histograms of a measure. The technical design uses the FloPoCo (Floating‐Point Cores) framework with customized arithmetic operators; the computation block is a pipelined architecture, which computes a new value of the flatness in each clock cycle. The design and implementation achieve optimization directives of the FPGA resources relevant for operation in space, like area, energy efficiency, and precision. The technology was tested in laboratory using Xilinx SRL16 or SRLC32 macros and provides correct results validated with test time series provided by magnetic field data collected in the solar wind by ULYSSES spacecraft. The characteristics and performance of the laboratory prototype pave the way for a space qualified version of the laboratory design.

Coordination within the remote sensing payload on the Solar Orbiter mission

Context.To meet the scientific objectives of the mission, the Solar Orbiter spacecraft carries a suite of in-situ (IS) and remote sensing (RS) instruments designed for joint operations with inter-instrument communication capabilities. Indeed, previous missions have shown that the Sun (imaged by the RS instruments) and the heliosphere (mainly sampled by the IS instruments) should be considered as an integrated system rather than separate entities. Many of the advances expected from Solar Orbiter rely on this synergistic approach between IS and RS measurements.Aims.Many aspects of hardware development, integration, testing, and operations are common to two or more RS instruments. In this paper, we describe the coordination effort initiated from the early mission phases by the Remote Sensing Working Group. We review the scientific goals and challenges, and give an overview of the technical solutions devised to successfully operate these instruments together.Methods.A major constraint for the RS instruments is the limited telemetry (TM) bandwidth of the Solar Orbiter deep-space mission compared to missions in Earth orbit. Hence, many of the strategies developed to maximise the scientific return from these instruments revolve around the optimisation of TM usage, relying for example on onboard autonomy for data processing, compression, and selection for downlink. The planning process itself has been optimised to alleviate the dynamic nature of the targets, and an inter-instrument communication scheme has been implemented which can be used to autonomously alter the observing modes. We also outline the plans for in-flight cross-calibration, which will be essential to the joint data reduction and analysis.Results.The RS instrument package on Solar Orbiter will carry out comprehensive measurements from the solar interior to the inner heliosphere. Thanks to the close coordination between the instrument teams and the European Space Agency, several challenges specific to the RS suite were identified and addressed in a timely manner.

The Solar Orbiter EUI instrument: The Extreme Ultraviolet Imager

Context.The Extreme Ultraviolet Imager (EUI) is part of the remote sensing instrument package of the ESA/NASA Solar Orbiter mission that will explore the inner heliosphere and observe the Sun from vantage points close to the Sun and out of the ecliptic. Solar Orbiter will advance the “connection science” between solar activity and the heliosphere.Aims.With EUI we aim to improve our understanding of the structure and dynamics of the solar atmosphere, globally as well as at high resolution, and from high solar latitude perspectives.Methods.The EUI consists of three telescopes, the Full Sun Imager and two High Resolution Imagers, which are optimised to image in Lyman-αand EUV (17.4 nm, 30.4 nm) to provide a coverage from chromosphere up to corona. The EUI is designed to cope with the strong constraints imposed by the Solar Orbiter mission characteristics. Limited telemetry availability is compensated by state-of-the-art image compression, onboard image processing, and event selection. The imposed power limitations and potentially harsh radiation environment necessitate the use of novel CMOS sensors. As the unobstructed field of view of the telescopes needs to protrude through the spacecraft’s heat shield, the apertures have been kept as small as possible, without compromising optical performance. This led to a systematic effort to optimise the throughput of every optical element and the reduction of noise levels in the sensor.Results.In this paper we review the design of the two elements of the EUI instrument: the Optical Bench System and the Common Electronic Box. Particular attention is also given to the onboard software, the intended operations, the ground software, and the foreseen data products.Conclusions.The EUI will bring unique science opportunities thanks to its specific design, its viewpoint, and to the planned synergies with the other Solar Orbiter instruments. In particular, we highlight science opportunities brought by the out-of-ecliptic vantage point of the solar poles, the high-resolution imaging of the high chromosphere and corona, and the connection to the outer corona as observed by coronagraphs.

Mission Data Processor Aboard the BepiColombo Mio Spacecraft: Design and Scientific Operation Concept

BepiColombo Mio, also known as the Mercury Magnetospheric Orbiter (MMO), is intended to conduct the first detailed study of the magnetic field and environment of the innermost planet, Mercury, alongside the Mercury Planetary Orbiter (MPO). This orbiter has five payload groups; the MaGnetic Field Investigation (MGF), the Mercury Plasma Particle Experiment (MPPE), the Plasma Wave Investigation (PWI), the Mercury Sodium Atmosphere Spectral Imager (MSASI), and the Mercury Dust Monitor (MDM). These payloads operate through the Mission Data Processor (MDP) that acts as an integrated system for Hermean environmental studies by the in situ observation of charged and energetic neutral particles, magnetic and electric fields, plasma waves, dust, and the remote sensing of radio waves and exospheric emissions. The MDP produces three kinds of coordinated data sets: Survey (L) mode for continuous monitoring, Nominal (M) mode for standard analyses of several hours in length (or more), and Burst (H) mode for analysis based on 4–20-min-interval datasets with the highest cadence. To utilize the limited telemetry bandwidth, nominal- and burst-mode data sets are partially downlinked after selections of data based on L- or L/M-mode data, respectively. Burst-mode data can be taken at preset timings, or by onboard automatic triggering. The MDP functions are implemented and tested on the ground as well as cruising spacecraft; they are responsible for conducting full scientific operations aboard spacecraft.

Onboard Automated CME Detection Algorithm for the Visible Emission Line Coronagraph on ADITYA-L1

ADITYA-L1 is India's first space mission to study the Sun from Lagrangian 1 position. { \textit{Visible Emission Line Coronagraph}} (VELC) is one of the seven payloads in ADITYA-L1 mission scheduled to be launched around 2020. One of the primary objectives of the VELC is to study the dynamics of coronal mass ejections (CMEs) in the inner corona. This will be accomplished by taking high resolution ($\approx$ 2.51 arcsec pixel$^{-1}$) images of corona from 1.05 R$_{\odot}$ -- 3 R$_{\odot}$ at high cadence of 1 s in 10 \AA\ passband centered at 5000 \AA. Due to limited telemetry at Lagrangian 1 position we plan to implement an onboard automated CME detection algorithm. The detection algorithm is based on the intensity thresholding followed by the area thresholding in successive difference images spatially re-binned to improve signal to noise ratio. We present the results of the application of this algorithm on the data from existing space- and ground-based coronagraph. Since, no existing space-based coronagraph has FOV similar to VELC, we have created synthetic coronal images for VELC FOV after including photon noise and injected different type of CMEs. The performance of CME detection algorithm is tested on these images. We found that for VELC images, the telemetry can be reduced by a factor of 85\% or more keeping CME detection rate of 70\% or above at the same time. Finally, we discuss the advantages and disadvantages of this algorithm. The application of such onboard algorithm in future will enable us to take higher resolution images with improved cadence from space and also reduce the load on limited telemetry at the same time. This will help in better understanding of CMEs by studying their characteristics with improved spatial and temporal resolutions.

Intelligent Sampling of Hazardous Particle Populations in Resource‐Constrained Environments

AbstractSampling of anomaly‐causing space environment drivers is necessary for both real‐time operations and satellite design efforts, and optimizing measurement sampling helps minimize resource demands. Relating these measurements to spacecraft anomalies requires the ability to resolve spatial and temporal variability in the energetic charged particle hazard of interest. Here we describe a method for sampling particle fluxes informed by magnetospheric phenomenology so that, along a given trajectory, the variations from both temporal dynamics and spatial structure are adequately captured while minimizing oversampling. We describe the coordinates, sampling method, and specific regions and parameters employed. We compare resulting sampling cadences with data from spacecraft spanning the regions of interest during a geomagnetically active period, showing that the algorithm retains the gross features necessary to characterize environmental impacts on space systems in diverse orbital regimes while greatly reducing the amount of sampling required. This enables sufficient environmental specification within a resource‐constrained context, such as limited telemetry bandwidth, processing requirements, and timeliness.

One-bit compressed sensing reconstruction for block sparse signals

Data compression is crucial for resource-constrained signal acquisition and wireless transmission applications with limited data bandwidth. In such applications, wireless data transmission dominates the energy consumption, and the limited telemetry bandwidth could be overwhelmed by the large amount of data generated from multiple sensors. Conventional data compression techniques are computationally intensive, consume large silicon area and offset the energy benefits from reduced data transmission. Recently, compressed sensing (CS) has shown potential in achieving compression performance comparable to previous methods but it has simpler hardware. Especially, one-bit CS theory proves that the signs of compressed measurements contain sufficient information about signal reconstruction, gives that the signals are sparse or compressible in specific dictionaries, thus demonstrating its potential in energy-constrained signal recording and wireless transmission applications. However, the sparsity assumption is too restrictive in many actual scenarios, especially when it is difficult to seek sparse representation for signals. In this paper, a novel one-bit CS method is proposed to reconstruct the signals that are difficult to represent with traditional sparse models. It is capable of recovering signal with comparable compression ratio but avoiding the dictionary selection procedure.The proposed method consists of two parts. 1) The block sparse model is adopted to enforce the structured sparsity of the signals. It not only overcomes the drawbacks of conventional sparse models but also enhances the signal representation accuracy. 2) The probabilistic model of one-bit CS procedure is constructed. Because of the existence of logistic function in probabilistic model of one-bit CS, the Bayesian inference cannot be used to proceed, and the variational Bayesian inference algorithm is developed to reconstruct the original signals from one-bit measurements.Various experiments on different quantities of compressed measurements and iterations are carried out to evaluate the recovery performance of the proposed approach. The photoplethysmography (PPG) signals recorded from subject wrist (dorsal locations) by using PPG sensors built in a wristband are selected as the validation data because they are difficult to represent with traditional sparse dictionaries. The experimental results reveal that the proposed approach outperforms the state-of-the-art one-bit CS method in terms of both reconstruction accuracy and convergence rate.Compared with prior method on one-bit CS, the proposed method shows competitive or superior performance in three aspects. Firstly, by adopting the block sparse model, the proposed method improves the capability to compress signals that are difficult to represent with traditional sparse models, thus making it more practical for long term and real applications. Secondly, by embedding the statistical properties of the one-bit measurements into the recovery algorithm, the proposed method outperforms other one-bit CS methods in terms of both reconstruction performance and convergence speed. Finally, energy and computational efficiency of the proposed method make it an ideal candidate for resource-constrained, large scale, multiple channel signal acquisition and transmission applications.

JPEG2000 Image Compression on Solar EUV Images

For future solar missions as well as ground-based telescopes, efficient ways to return and process data have become increasingly important. Solar Orbiter, e.g., which is the next ESA/NASA mission to explore the Sun and the heliosphere, is a deep-space mission, which implies a limited telemetry rate that makes efficient onboard data compression a necessity to achieve the mission science goals. Missions like the Solar Dynamics Observatory (SDO) and future ground-based telescopes such as the Daniel K. Inouye Solar Telescope, on the other hand, face the challenge of making petabyte-sized solar data archives accessible to the solar community. New image compression standards address these challenges by implementing efficient and flexible compression algorithms that can be tailored to user requirements. We analyse solar images from the Atmospheric Imaging Assembly (AIA) instrument onboard SDO to study the effect of lossy JPEG2000 (from the Joint Photographic Experts Group 2000) image compression at different bit rates. To assess the quality of compressed images, we use the mean structural similarity (MSSIM) index as well as the widely used peak signal-to-noise ratio (PSNR) as metrics and compare the two in the context of solar EUV images. In addition, we perform tests to validate the scientific use of the lossily compressed images by analysing examples of an on-disk and off-limb coronal-loop oscillation time-series observed by AIA/SDO.

ADAHELI+: exploring the fast, dynamic Sun in the x-ray, optical, and near-infrared

Advanced Astronomy for Heliophysics Plus (ADAHELI+) is a project concept for a small solar and space weather mission with a budget compatible with an European Space Agency (ESA) S-class mission, including launch, and a fast development cycle. ADAHELI+ was submitted to the European Space Agency by a European-wide consortium of solar physics research institutes in response to the Call for a small mission opportunity for a launch in 2017, of March 9, 2012. The ADAHELI+ project builds on the heritage of the former ADAHELI mission, which had successfully completed its phase-A study under the Italian Space Agency 2007 Small Mission Programme, thus proving the soundness and feasibility of its innovative low-budget design. ADAHELI+ is a solar space mission with two main instruments: ISODY+: an imager, based on Fabry-Perot interferometers, whose design is optimized to the acquisition of highest cadence, long-duration, multiline spec- tropolarimetric images in the visible/near-infrared region of the solar spectrum. XSPO: an x-ray polarimeter for solar flares in x-rays with energies in the 15 to 35 keV range. ADAHELI+ is capable of performing observations that cannot be addressed by other currently planned solar space missions, due to their limited telemetry, or by ground-based facilities, due to the problematic effect of the terrestrial atmosphere.©TheAuthors.PublishedbySPIEunder

Incremental locally linear embedding-based fault detection for satellite attitude control systems

This paper presents a novel fault detection method based on incremental locally linear embedding (I-LLE) to improve the accuracy of fault detection for a satellite with high-dimensional telemetry data. Firstly, the I-LLE algorithm is introduced, followed by an application on Satellite “TX-1” telemetry to extract the low-dimensional features, which can be used to perform fault detection with statistical indexes. A rapid semi-physical platform for satellite attitude control systems based on PC104 and AD7011-EVA is designed to perform fault simulation, because limited telemetry contains fewer fault patterns, which renders fault simulation for in-orbit satellites difficult. The I-LLE-based fault detection scheme is then employed to detect anomalies in simulation data. Simulation results presented in this paper validate the fault detection scheme.

The Axial Double Probe and Fields Signal Processing for the MMS Mission

The Axial Double Probe (ADP) instrument measures the DC to ∼100 kHz electric field along the spin axis of the Magnetospheric Multiscale (MMS) spacecraft (Burch et al., Space Sci. Rev., 2014, this issue), completing the vector electric field when combined with the spin plane double probes (SDP) (Torbert et al., Space Sci. Rev., 2014, this issue, Lindqvist et al., Space Sci. Rev., 2014, this issue). Two cylindrical sensors are separated by over 30 m tip-to-tip, the longest baseline on an axial DC electric field ever attempted in space. The ADP on each of the spacecraft consists of two identical, 12.67 m graphite coilable booms with second, smaller 2.25 m booms mounted on their ends. A significant effort was carried out to assure that the potential field of the MMS spacecraft acts equally on the two sensors and that photo- and secondary electron currents do not vary over the spacecraft spin. The ADP on MMS is expected to measure DC electric field with a precision of ∼1 mV/m, a resolution of ∼25 μV/m, and a range of ∼±1 V/m in most of the plasma environments MMS will encounter. The Digital Signal Processing (DSP) units on the MMS spacecraft are designed to perform analog conditioning, analog-to-digital (A/D) conversion, and digital processing on the ADP, SDP, and search coil magnetometer (SCM) (Le Contel et al., Space Sci. Rev., 2014, this issue) signals. The DSP units include digital filters, spectral processing, a high-speed burst memory, a solitary structure detector, and data compression. The DSP uses precision analog processing with, in most cases, >100 dB in dynamic range, better that −80 dB common mode rejection in electric field (E) signal processing, and better that −80 dB cross talk between the E and SCM (B) signals. The A/D conversion is at 16 bits with ∼1/4 LSB accuracy and ∼1 LSB noise. The digital signal processing is powerful and highly flexible allowing for maximum scientific return under a limited telemetry volume. The ADP and DSP are described in this article.

Highly Scalable Amplified Hybrid TDM/DWDM Array Architecture for Interferometric Fiber-Optic Sensor Systems

We present a distributed amplified hybrid dense wavelength division multiplexing (DWDM) and time division multiplexing (TDM) array architecture for large scale interferometric fiber-optic sensor array systems. This architecture employs a distributed Erbium doped fiber amplifier (EDFA) scheme to decrease the distribution loss among multiplexed wavelengths, and employs TDM at each wavelength to increase the total number of sensors that can be supported. The first experimental demonstration of this system is reported including results which show the potential for multiplexing and interrogating up to 4096 sensors using a single telemetry fiber pair with good system performance. The number of interrogation sensors could be further increased by increasing the number of wavelength channels. These architectures would be of great importance in the application of systems requiring very large number of sensors with limited telemetry cabling.

Focusing on Size and Energy Dependence of Electron Microbursts From the Van Allen Radiation Belts

Focusing on Size and Energy Dependence of Electron Microbursts From the Van Allen Radiation Belts

A Fully Implantable, Programmable and Multimodal Neuroprocessor for Wireless, Cortically Controlled Brain-Machine Interface Applications

Reliability, scalability and clinical viability are of utmost importance in the design of wireless Brain Machine Interface systems (BMIs). This paper reports on the design and implementation of a neuroprocessor for conditioning raw extracellular neural signals recorded through microelectrode arrays chronically implanted in the brain of awake behaving rats. The neuroprocessor design exploits a sparse representation of the neural signals to combat the limited wireless telemetry bandwidth. We demonstrate a multimodal processing capability (monitoring, compression, and spike sorting) inherent in the neuroprocessor to support a wide range of scenarios in real experimental conditions. A wireless transmission link with rate-dependent compression strategy is shown to preserve information fidelity in the neural data. At 32 channels, the neuroprocessor has been fully implemented on a 5mm×5mm nano-FPGA, and the prototyping resulted in 5.19 mW power consumption, bringing its performance within the power-size constraints for clinical use. The optimal design for compression and sorting performance was evaluated for multiple sampling frequencies, wavelet basis choice and power consumption.

Cost‐effectiveness of Telemetry for Hospitalized Patients With Low‐risk Chest Pain

The majority of chest pain admissions originate in the emergency department (ED). Despite a low incidence of cardiac events, limited telemetry availability, and its questionable benefit, these patients are routinely admitted to a monitored setting. The objectives were to analyze the cost-effectiveness of admission to telemetry versus admission to an unmonitored hospital bed in low-risk chest pain patients and explore when the use of telemetry may be cost-effective. The authors constructed a decision analytic model to evaluate the scenario of an ED admission of an otherwise healthy 55-year-old patient with low-risk chest pain defined as an acute coronary syndrome (ACS) probability of 2%. Costs were estimated from 2009 Medicare data for hospital reimbursement and physician services, as well as published data on disability costs. Published studies were used to estimate the risk of ACS, cardiac arrest, time to defibrillation, survival, long-term disability, and quality of life. In the base case, telemetry was more effective (0.0044 quality-adjusted life-years [QALYs]) but more costly ($299.67) than a floor bed, resulting in a high marginal cost-effectiveness ratio (mCER) of $67,484.55 per QALY. In comprehensive sensitivity analyses, the mCER crossed below the willingness-to-pay (WTP) threshold of $50,000 per QALY when the following scenarios were met: the probability of ACS exceeds 3%, the probability of cardiac arrest is greater than 0.4%, the probability of shockable dysrhythmia is above 83%, the probability of delay in telemetry bed availability is below 52%, and the opportunity cost of delay to telemetry bed placement is below $119. Telemetry may be a "cost-effective" use of health care resources for chest pain patients when patients have a probability of ACS above 3% or for patients with a minimal delay and cost associated with obtaining a monitored bed. Further research is needed to better stratify low-risk chest pain patients to the appropriate inpatient setting and to understand the frequency and costs associated with delays in obtaining monitored beds.

Mind your P's and Q's

Mind your P's and Q's

Use of microphones to record windspeed and turbulence in planetary environments

A major feature of any planetary acoustic measurement is noise due to ambient winds, or to the motion of the measurement platform through the air. Venera 13 and 14 recorded sound on the surface of Venus: the amplitude of the microphone signal was interpreted (by dynamic pressure scaling) to recover a windspeed. The Huygens probe at Titan also recorded sound levels during descent and on the surface with a passive microphone and an acoustic sounder. The author has made passive microphone measurements made on a rotating aerospace vehicle (an instrumented Frisbee) which show spin modulation and a variation with flight speed and angle of attack. He has also used microphones as a crude wind sensor on an array of 20 meteorological stations used to study dust devils in Arizona. All of these observations will be reviewed. Lessons learned for future planetary measurements, and prospects and methods for microphonic anemometry (especially with limited telemetry bandwidth) will be discussed.

Early results from the Whisper instrument on Cluster: an overview

Abstract. The Whisper instrument yields two data sets: (i) the electron density determined via the relaxation sounder, and (ii) the spectrum of natural plasma emissions in the frequency band 2–80 kHz. Both data sets allow for the three-dimensional exploration of the magnetosphere by the Cluster mission. The total electron density can be derived unambiguously by the sounder in most magnetospheric regions, provided it is in the range of 0.25 to 80 cm-3 . The natural emissions already observed by earlier spacecraft are fairly well measured by the Whisper instrument, thanks to the digital technology which largely overcomes the limited telemetry allocation. The natural emissions are usually related to the plasma frequency, as identified by the sounder, and the combination of an active sounding operation and a passive survey operation provides a time resolution for the total density determination of 2.2 s in normal telemetry mode and 0.3 s in burst mode telemetry, respectively. Recorded on board the four spacecraft, the Whisper density data set forms a reference for other techniques measuring the electron population. We give examples of Whisper density data used to derive the vector gradient, and estimate the drift velocity of density structures. Wave observations are also of crucial interest for studying small-scale structures, as demonstrated in an example in the fore-shock region. Early results from the Whisper instrument are very encouraging, and demonstrate that the four-point Cluster measurements indeed bring a unique and completely novel view of the regions explored.Key words. Space plasma physics (instruments and techniques; discontinuities, general or miscellaneous)