Minimize Swarm Instruments Overview
Contents

Introduction

All the three Swarm satellite are equipped with a set of six instruments: Absolute Scalar Magnetometer (ASM), Vector Field Magnetometer (VFM), Star Tracker (STR), Electric Field Instrument (EFI), GPS Receiver (GPSR), and Accelerometer (ACC).

Figure 1: Swarm side annotation

Figure 1: Swarm side annotation

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Absolute Scalar Magnetometer (ASM)

Figure 2: ASM sensor

Figure 2: ASM sensor


The Absolute Scalar Magnetometer (ASM) measures the magnetic field intensity at the tip of the boom. The ASM is an absolute instrument, i.e. it is not subject to changes of its intrinsic parameters over time. It uses the PPS as the absolute, external reference. [AD-6] contains descriptions of the ASM intrinsic processing algorithms for both the nominal scalar mode and the experimental vector mode. Both modes generate scalar (magnetic field intensity) data; the processing of these is described in this chapter, including the system level algorithms for stray field correction. Vector data from the ASM vector mode (as well as burst mode data) are only provided as Level 1a data (the ASMXAUX_1B Level 1b Product contains additional data suited for the Level 1a ASM vector data).

ASM Algorithm Overview

The overall processing is sketched in the Figure below. First, the raw output (Level 1a.ASM. Sci.E, rate: 1 Hz, timestamps t0,ASM) from the ASM is converted to physical units (nT), corrected for the Bloch-Siegert effect, and corrected for delays in timestamps (from t0,ASM to tASM). This constitutes the Level 1bInst.ASM data, the ASM instrument Level 1b scalar product containing the perturbated magnetic field intensity measurements at corrected time instants, tASM. Note: this includes stray fields from the ASM itself.

Then outlier detection and/or rejection is performed. Followed by corrections for magnetic disturbances (stray fields) of the ASM itself, of the VFM, and of the rest of the spacecraft. These disturbances need to be filtered according to the intrinsic filter of the ASM instrument (see [AD-7] for a detailed description of ASM processing). This constitutes the fully calibrated and corrected scalar magnetic measurements, FASM, at instrument time instants (tASM). These data are then adjusted for the group delay of the ASM intrinsic filter, i.e. the measurements are shifted in time from tASM to tout,ASM.

Finally, these data are interpolated to yield the scalar elements of the Level 1b.Mag-L product at UTC seconds. The interpolation process also bridges small gaps (a few samples) in the ASM data stream typically caused by missing telemetry (missing ISP) or outlier rejection.

Figure 3: ASM processing overview

Figure 3: ASM processing overview

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Vector Field Magnetometer (VFM)

Figure 4: Swarm Optical Bench

Figure 4: Swarm Optical Bench

The Vector Field Magnetometer (VFM) measures the magnetic field vector at the tip of the optical bench on the boom. The sensor is a 3-axis Compact Spherical Coil (CSC) with a 3-axis Compact Detector Coil (CDC) inside. The instrument operates as a closed-loop system adjusting the compensating CSC currents to maintain a null field at the detector coils within the sphere. The currents in the CSC coils are measured and digitized (by an ADC) and this constitutes the raw measurements of the instrument. See [AD-8] for a detailed description of the instrument, and for the Level 1b algorithm described by the instrument supplier.

The VFM is an analogue instrument and as such subject to temporal changes due to radiation and aging effects of the electronics. The effects are only significant in the bias and linear scale parameters of the characterization; hence these parameters are estimated daily through a comparison of the VFM output with the ASM scalar magnetometer output. Additionally, the non-orthogonality angles of the VFM sensor may also be estimated in this process. The allowed change from day to day in the parameters is controlled group-wise by weight parameters specified in the CCDB. The parameters estimated daily are stored in a Temporal Calibration File (TCF) as an auxiliary data product.

VFM Algorithm Overview

The overall VFM processing is sketched in the Figure below. Only data with a common DPU_id is to be processed, minority data (DPU_id wise) is rejected. Next, the raw output (Level 1a.VFM.Sci.EU, rate: 50 Hz, timestamps t0,VFM) of the VFM is corrected for timestamp, processing, and filter delays. Then, it is corrected and converted to physical units (nT) using the CCDB.VFM.Cal parameters and the Level 1a.VFM.Sci.TX temperatures. This is the Level 1bInst VFM vector product. The rate is 50 Hz and the time-instants tVFM.

Then, the preliminary vector field measurements, B'VFM, are computed using the TCF.VFMinit parameters. TCF.VFMinit is the most recent (w.r.t. data being processed) TCF.VFM record among the TCF.VFMinput (from the previous Level 1b Product) and the CCDB.L1BP. VFM.TCF_Aux array - with DPU_id corresponding to Level 1a.VFM.Sci.DPU_id. Formally, let t0 = Level 1a.VFM.Sci.t0, then:

Next, outliers are detected and accordingly rejected or flagged as suspicious samples. Now, the magnetic stray fields from the rest of the S/C at the VFM sensor position - at the time instants of the VFM measurements, tout,VFM (= tVFM) - are computed. The phase linearity and fast response of the VFM Bessel filter makes it unnecessary to apply a filter to the stray fields as was the case for the ASM. However, the characterization of the AOCS torquer coil disturbances possibly needs to take the VFM filter into account.

Next, the internal temporal changes of the VFM electronics and possibly any change in the non-orthogonalities of the CSC are modeled by the TCF.VFM parameters which are estimated by comparison of VFM data with the fully corrected ASM scalar data (FASM). The new estimates of the TCF.VFM parameters, TCF.VFMoutput, are applied to all the VFM data of the actual day. Together with the correction for stray magnetic fields the Level 1b.Mag-H.BVFM data are obtained. I.e. fully converted and corrected magnetic vector data in the orthogonal VFM sensor frame. The rate is 50 Hz and the time instants tout,VFM.

Then Level 1b.Mag-L.BVFM, the 1 Hz magnetic vector product in the VFM frame at UTC seconds, is extracted. Finally, the magnetic field vectors BVFM at 50 Hz and 1 Hz are transformed via the Common Reference Frame (CRF) into the NEC frame. This completes the generation of the Level 1b.Mag-H.BNEC and Level 1b.Mag-L.BNEC products.

Note: the rotation from the VFM to the CRF frame is estimated pre-flight and refined inflight. Hence periodic updates of CCDB.Structure.STR_q_VFM are foreseen and consequently reprocessing of the final step above is required regularly.

Figure 5: VFM processing overview

Figure 5: VFM processing overview

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Star Tracker (STR)

The Star Tracker (STR) is comprised of three Camera Head Units (CHUs) mounted on the innermost end of the optical bench. Nominally, the attitudes of all three heads are provided simultaneously at 1 Hz rate, however one head is regularly blinded by the Sun leaving the attitudes of just two heads. The attitudes of the 2-3 CHU are combined into one attitude, the attitude of the STR Common Reference Frame (CRF). The combination uses the method described in [RD-2]. The attitudes of CRF are then interpolated to obtain the CRF and S/C attitudes at required time instants: 50 Hz VFM measurements, 2 Hz EFI measurements and UTC seconds.

STR Algorithm Overview

First, the time-stamps are corrected for any delays: tout,STR = t0,STR - CCDB.STR.Delay. Then, the aberrational correction is verified and if necessary applied. The valid attitudes of the STR are combined into common attitude solutions, qCRF←ICRF, providing the CRF → ICRF transformations. This is the Level 1bInst.STR product. Then these are interpolated to the time instants to be used (UTC seconds, tout,VFM, etc.) using a smoothing, cubic B-spline method. Finally, the various required output transformations are generated by combining series of transformations.

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Electric Field Instruments (EFI)

Figure 6: Electric Field Instruments

Figure 6: Electric Field Instruments

The Electric Field Instrument determines the ion density, the ion drift velocity, and the electric field at the S/C front panel (in-flight). The instrument consists of two components: the Langmuir Probe (LP) and the Thermal Ion Imager (TII).

EFI Algorithm Overview

The detailed descriptions of the algorithms are formed in two documents:

A) The Langmuir Probe (LP) algorithms can be found in [AD-9],

B) The Thermal Ion Imager algorithms can be found in [AD-10].

The S/C ephemeris and magnetic field vector data needed by the EFI algorithms are taken from various sources:

  • The position is taken from Level 1b.Mag-L to co-locate plasma data with magnetic data (the ca. 7 m discrepancy between rEFI and rVFM is ignored). Interpolation in time is done using cubic Lagrange interpolation.
  • The velocity is taken from Level 1b.Eph. The transformation of this from the ITRF to the NEC frame is given by
    vNEC = RNEC←ITRF vITRF
    where the transformation matrix RNEC←ITRF is defined in Appendix ...
  • The transformation from the S/C frame to the NECVFM frame is given by qITRF←S/C ⊗ qNEC←ITRF, see also [AD-7] (the difference between the NECVFM and NECEFI frame is less than 1/3" and is ignored).
  • The magnetic field vector is taken from the Level 1b.Mag-H.BNEC.

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GPS Receiver (GPSR)

Through the GPS antenna, the GPS receiver (GPSR) receives the signals from all of the antenna visible GPS satellites. The L1b processing corrects for known effects related to the Swarm instruments and satellite. The external errors e.g. due to the GPS segment are corrected in the orbit determination processing.

Eleven different input packet definitions from the ISP exists, these are

MDH, Measurement Data Header format
CAP, Carrier Phase data record
CAA, Carrier Amplitude data record
COP, Code Phase data record
GNA, GPS Nav Almanac data record
GNU, GPS Nav UTC and Ionosphere data record
MNS, Minimum Navigation Solution data record
IGC, IMT/GPST Correlation data record
GNE, GPS Nav Ephemeris data record
CS, Constellation Status record
AUX, Swarm Auxiliary data record

However, for the GPS algorithms processing only seven of them are used. The collection of the data record from the CAP, CAA, COP, and GNE has to be repeated N times for the N viewed satellites with a 0.1 Hz update frequency.

GPSR Algorithm Overview

The processing flow of algorithms is separated into three major steps:

  • L0 processing, which comprises reading and checking of the raw binary level 0 instrument data.
  • L1a processing, which comprises reformatting as well as interpretation and unit conversions of the L0 ISPs. The result is stored as L1a products.
  • L1b processing, which comprises correction of the L1a data corresponding to the characterized distortions comprised in the Instrument Characterization Data Base (ICDB) which will be a part of the CCDB. The result is stored as RINEX 3.00 formatted ASCII data.

The overall data flow from L0 to L1b is shown in the figure below. An overview of the sequential walk-through of the data flow can be found in [AD-7].

Figure 7: Level 0 to Level 1b processing flow for GPSR

Figure 7: Level 0 to Level 1b processing flow for GPSR

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Accelerometer (ACC)

The Level 1b instrument processing of the Accelerometer (ACC) is described in [AD-7] and briefly repeated here.

Algorithm overview

The intrinsic ACC processing is described in [AD-11], cf. Appendix L in [AD-7]. The Level 1a data comprising the acceleration vectors (linear and rotational) in engineering units (eu) and the required house-keeping information (e.g. temperatures and polarization voltage) in physical units. The Level 1a data shall (optionally, i.e. user selectable) be stored as Level 1a Products.

The processing of Level 1a data to Level 1b ACC data is sketched in the Figure below.

Figure 8: ACC processing overview

Figure 8: ACC processing overview

It consists of the following tasks:

  • Correct for delays
  • Identification of spurious samples, flag measurements accordingly
  • Determine satellite events with possible impact on ACC measurements (e.g. thruster firing, magnetic torquer operation, heater switching) and flag ACC measurements accordingly
  • Conversion of ACC measurements (and their linear estimates) from engineering units (eu) to physical units
  • Rotation of accelerations from ACC frame to S/C frame
  • Calculate and possibly (depending on processor configuration) apply correctional terms

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