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Compression and Prioritization

A surface rover produces far more data than its downlink can carry in a sol, on a link whose rate is itself set by antenna geometry, the deep space network schedule and Mars-Earth range rather than by anything onboard. Every camera on Spirit and Opportunity produced a 1024x1024 image at 12 bits per pixel, and the average returned rate was 1.13 bits per pixel [1]. That ratio, roughly ten to one, is what made a Mars imaging mission possible on a link that returns about 56 Mb/sol. Reducing the byte count is only half the problem; the other half is deciding, sol by sol and pass by pass, which of the products worth sending goes first when not everything will fit. What is compressed, how hard, and in what order it is sent are three separate decisions, made in the flight compressor’s design, in ground-set byte quotas, and in a priority table the operations team revises for every communication window.

MER carries three: ICER for lossy and progressive compression, a modified LOCO for lossless, and LZO for engineering data [7]. Sojourner’s Mars Pathfinder used a Rice compressor and JPEG [2]. One Pathfinder color mosaic used a 24:1 ratio on the red filter image [9] and 48:1 on the green and blue images [9]. ICER’s wavelet-based progressive stream degrades gracefully under packet loss in a way a block-transform codec does not, and it gives an operations team a byte-quota knob tied directly to output size.

ICER is wavelet-based and progressive: the compressed stream is organized so that reconstructions of successively higher quality can be produced as more of it arrives [1]. It partitions the image into independent error-containment segments so that a lost packet damages only its segment, which mattered because a fair number of MER packets were lost. Its parameters are the wavelet filter, the number of decomposition stages, the number of error-containment segments, the byte quota and a minimum loss parameter.

LOCO exists alongside it because although ICER can compress losslessly, LOCO’s simple predictive approach is several times faster at similar effectiveness [1]. On six Mars Pathfinder test images at 12 bits per pixel, lossless rates averaged 8.78 bits/pixel for ICER, 8.84 for LOCO, 9.10 for JPEG 2000 and 9.36 for the CCSDS Rice compressor; the Rice implementation actually used by Pathfinder was worse still, ranging from 9.38 to 10.61 bits/pixel across the five single-frame images [2]. On the same images companded to 8 bits, ICER and LOCO both averaged 5.02 bits/pixel against 5.22 for JPEG 2000 and 5.52 for CCSDS Rice.

As of 7 February 2004 [1]:

CompressorImage typeImagesCombined area, MpixelVolume, MBAverage rate, bits/pixel
ICERregular51322867.9387.31.13
ICERthumbnail607524.93.81.27
LOCOregular, lossless489124.592.76.24
LOCOreference pixels111436.59.22.12
noneregular44.26.012.00

Source: [1], Table 1. Four images in the entire set were returned uncompressed. Lossless LOCO at 6.24 bits/pixel costs about five and a half times the volume of the ICER default, so it was reserved for cases where fidelity was the point [1].

Parameter selection varied by camera and by purpose [1]. Panoramic camera full frames on Spirit used 3 or 4 decomposition stages, wavelet filters A or E, 1 to 20 segments, and averaged 1.12 bits/pixel over 1014 images. Navigation camera full frames used 12 to 20 segments and averaged 0.97 bits/pixel over 235 images, the lowest rate of any full frame category, because navigation images are not science products [1]. Microscopic Imager frames took 24 to 32 segments and averaged 1.34 bits/pixel on Spirit and 2.36 on Opportunity. Hazard camera full frames used 16 to 32 segments, the highest segment counts, because they are the images a lost packet can least afford to damage [1].

Two mechanisms reduce volume before compression runs. Images are companded from 12 to 8 bits per pixel to improve fidelity in dark regions, which is worthwhile because the sensor noise is signal dependent [1]. Every acquired image also produces a 64x64 thumbnail by averaging 16x16 blocks, ICER-compressed to about 650 bytes, which is about 0.005 bits per pixel of the original; thumbnails preview full images that may not be sent for some time. Beyond that, MER sends subframes of interest at full quality with the whole frame at much lower quality, performs pixel averaging, and sends row sums, column sums or histograms alone.

Timing for the MER implementation of ICER was measured under VxWorks on a 20 MHz RAD6000 identical to the flight units [2]. Three results hold regardless of the absolute scale: compression is faster when fewer compressed bytes are produced, the time at a bit rate of zero is essentially the cost of the wavelet decomposition alone, and the choice of wavelet filter and the number of decomposition stages have little effect on speed. The published figure gives compression time against output rate for a 1024x1024 test image with one error-containment segment, but its vertical axis is labeled in milliseconds per pixel, which cannot be literal at this image size, so the absolute value is not usable from the open document [2].

The byte quota does not give exact control over output size. ICER checks the quota only between compression of segments of subband bit planes, and does not account for the backlog still held in the segments’ interleaved entropy coders, so the output almost always exceeds the quota when the quality goal is not reached [2]. The overshoot depends on the segment count through two competing effects: more segments mean a larger total coder backlog, but also more frequent quota checks, so overshoot is minimized at a moderate segment count. MER controlled quality with the byte quota alone, setting the minimum loss parameter to zero, and transmitted the entire bitstream rather than truncating to the exact target, because truncation produces small quality variations between segments [1].

CCSDS publishes two relevant Blue Books: Image Data Compression, CCSDS 122.0-B-2, and Lossless Data Compression, CCSDS 121.0-B-3, the latter being the Rice-based algorithm that appears in the comparison above [5][6]. ICER-3D extends the ICER approach to hyperspectral imagery by compressing across the spectral dimension as well as the spatial ones [3]. No Mars surface vehicle has flown the CCSDS image compression standard; the flight compressors are mission-specific.

MSL kept the mission-specific pattern but moved back toward a standard codec for its Mastcams and Descent Imager: most Mastcam and MARDI images are downlinked as lossy JPEG, compressed onboard when the scientific need for full fidelity does not outweigh the downlink volume it costs, with a lossless mode available separately for the cases that need it [10]. That is a narrower design than MER’s: one general-purpose codec with a selectable quality setting [10], rather than a wavelet compressor tuned per camera and per segment count.

Compression of non-image data is a separate, quieter problem that the imaging literature does not cover. On Mars 2020, GZIP compression of non-image telemetry removed more than two thirds of the volume actually generated in the first 216 sols, taking 88.8 Gibit of source data down to 27.5 Gibit on the link, against a daily total data return of 1.5 to 2 Gibit per sol [11]. That is compression applied to housekeeping and engineering products, not camera frames, and it exists because a rover generates far more non-image telemetry than any single downlink pass can carry either. The link that has to carry it is itself limited: the M2020 UHF return link tops out at 2048 kbit/s with LDPC encoding [11].

Priority on MER is a property of the data product and it is set and revised from the ground. Each communication window command carries the durations for the real-time and recorded data priority tables along with start time, duration, antenna, rates and hardware configuration, and the window executes inside the communications behavior part of the flight software rather than through the sequence engine [4]. Data products carry a priority in their metadata file alongside collection time [8].

Onboard data organization places the highest priority playback data, fault and warning event reports and spacecraft health reports, earliest in a direct-to-Earth pass [4]. That ordering interacts with receiver lockup: lockup takes about 1 minute for high gain antenna rates but varies from pass to pass, so the project must plan a lockup allowance before the valuable playback starts. Too short and sent data is lost; too long and less data fits. The comm window lockup parameter was changed from 1 minute to 3 minutes for downlink rates of 3160 bit/s and higher, and 3 minutes consumes 10 percent of the return capacity of a 30 minute window; it was reduced to 2 minutes for some windows in the later extended missions [4].

Reprioritization is a routine operations activity. UHF reports were generated for every Odyssey pass at low priority in the extended mission by attaching a report sequence to the start of window preparation; to actually return one, data management issued a command raising its priority. Reports were reprioritized every seventh sol so telecom could spot-check relay performance, could be raised individually for interesting passes, and were marked for automatic deletion after 7 sols [4].

Priority also serves fault diagnosis. During the Spirit sol 18 flash anomaly a high priority communication window overrode the 10 bit/s fault default to give 40 or 300 bit/s on the low gain antenna, and the repeating event reports that came down at that rate are what first pointed at the flash memory [4].

The MER compression numbers are drawn from a fixed operational snapshot: the vehicle-wide totals are as of a single date in February 2004, and the earlier per-image test that justified choosing ICER over LOCO and JPEG 2000 used six Pathfinder images, five of them the same scene from one camera, with the authors stating outright that the filter ranking may not hold for other image types [1][2]. No compression time figure from the flight processor survives with a usable absolute scale; the published curve is mislabeled and only the qualitative relationships it shows are usable [2]. The ICER-3D hyperspectral results are airborne AVIRIS data, not a flight compressor running on any space vehicle, and its own authors show it losing to a simpler compressor in the lossless case [3]. No source cited above gives a byte-quota overshoot statistic, a rate-distortion or image-quality number for any flown compressor, or a packet loss rate for MER’s downlink; the interaction between segment count and overshoot is described only qualitatively [1][2]. The priority and lockup mechanics are reconstructed from a single mission’s operations account, written by the team that ran it, so the generalization from MER’s tables and lockup allowances to other missions’ downlink scheduling is not demonstrated here [4].

References

  1. Kiely, A. and Klimesh, M. (2004). Preliminary Image Compression Results from the Mars Exploration Rovers . IPN Progress Report. Source
    BibTeX
    @article{kiely2004preliminary,
      title = {Preliminary Image Compression Results from the Mars Exploration Rovers},
      author = {Kiely, A. and Klimesh, M.},
      journal = {IPN Progress Report},
      volume = {42-156},
      institution = {Jet Propulsion Laboratory},
      year = {2004},
      url = {https://ipnpr.jpl.nasa.gov/progress_report/42-156/156I.pdf}
    }
  2. Kiely, A. and Klimesh, M. (2003). The ICER Progressive Wavelet Image Compressor . IPN Progress Report. Source
    BibTeX
    @article{kiely2003icer,
      title = {The ICER Progressive Wavelet Image Compressor},
      author = {Kiely, A. and Klimesh, M.},
      journal = {IPN Progress Report},
      volume = {42-155},
      institution = {Jet Propulsion Laboratory},
      year = {2003},
      url = {https://ipnpr.jpl.nasa.gov/progress_report/42-155/155J.pdf}
    }
  3. Kiely, A., Klimesh, M., Xie, H. and Aranki, N. (2006). ICER-3D: A Progressive Wavelet-Based Compressor for Hyperspectral Images . IPN Progress Report. Source
    BibTeX
    @article{kiely2006icer3d,
      title = {ICER-3D: A Progressive Wavelet-Based Compressor for Hyperspectral Images},
      author = {Kiely, A. and Klimesh, M. and Xie, Heping and Aranki, N.},
      journal = {IPN Progress Report},
      volume = {42-164},
      institution = {Jet Propulsion Laboratory},
      year = {2006},
      url = {https://ipnpr.jpl.nasa.gov/progress_report/42-164/164A.pdf}
    }
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    BibTeX
    @incollection{taylor2014mars,
      title = {Mars Exploration Rover Telecommunications},
      author = {Taylor, Jim and Makovsky, Andre and Barbieri, Andrea and Tung, Ramona and Estabrook, Polly and Thomas, A. Gail},
      booktitle = {Deep Space Communications},
      series = {DESCANSO Design and Performance Summary Series},
      publisher = {Jet Propulsion Laboratory, California Institute of Technology},
      chapter = {7},
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    BibTeX
    @techreport{ccsds2017image,
      title = {Image Data Compression},
      author = {{CCSDS}},
      number = {CCSDS 122.0-B-2, Blue Book},
      institution = {Consultative Committee for Space Data Systems},
      year = {2017},
      url = {https://ccsds.org/Pubs/122x0b2e1.pdf}
    }
  6. CCSDS. (2020). Lossless Data Compression . Consultative Committee for Space Data Systems, CCSDS 121.0-B-3, Blue Book. Source
    BibTeX
    @techreport{ccsds2020lossless,
      title = {Lossless Data Compression},
      author = {{CCSDS}},
      number = {CCSDS 121.0-B-3, Blue Book},
      institution = {Consultative Committee for Space Data Systems},
      year = {2020},
      url = {https://ccsds.org/Pubs/121x0b3.pdf}
    }
  7. Reeves, G. E. (2005). An Overview of the Mars Exploration Rovers Flight Software . IEEE International Conference on Systems, Man and Cybernetics. Source
    BibTeX
    @inproceedings{reeves2005overview,
      title = {An Overview of the Mars Exploration Rovers Flight Software},
      author = {Reeves, Glenn E.},
      booktitle = {IEEE International Conference on Systems, Man and Cybernetics},
      volume = {1},
      pages = {1-7},
      address = {Waikoloa, Hawaii},
      year = {2005},
      doi = {10.1109/icsmc.2005.1571113},
      abstract = {The Mars exploration rovers (MER) flight software (FSW) is possibly the most complex software implementation to be deployed on another planet. The requirements dictated a software system that addressed four distinct mission phases (cruise, landing, egress, and surface) and the mission demanded a system with significant autonomy. The structure of the MER flight software reflects its object-oriented beginnings and the overall function reflects the requirements of the MER mission and spacecraft. This paper provides an overview of the function and structure of the MER flight software. The MER mission and spacecraft are briefly discussed to provide context for the flight software decomposition and the discussion of the software execution model.}
    }
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    BibTeX
    @inproceedings{reeves2005mars,
      title = {The Mars Rover Spirit FLASH Anomaly},
      author = {Reeves, Glenn E. and Neilson, Tracy A.},
      booktitle = {IEEE Aerospace Conference},
      pages = {4186-4199},
      address = {Big Sky, Montana},
      year = {2005},
      doi = {10.1109/aero.2005.1559723},
      abstract = {The Mars Exploration Rover "Spirit" suffered a debilitating anomaly that prevented communication with Earth for several anxious days. With the eyes of the world upon us, the anomaly team used each scrap of information, our knowledge of the system, and sheer determination to analyze and fix the problem, then return the vehicle to normal operation. This paper will discuss the Spirit FLASH anomaly, including the drama of the investigation, the root cause and the lessons learned from the experience}
    }
  9. Golombek, M. P., Anderson, R. C., Barnes, J. R., Bell, J. F., Bridges, N. T., Britt, D. T., Brückner, J., Cook, R. A., Crisp, D., Crisp, J. A., Economou, T., Folkner, W. M., Greeley, R., Haberle, R. M., Hargraves, R. B., Harris, J. A., Haldemann, A. F. C., Herkenhoff, K. E., Hviid, S. F., Jaumann, R., Johnson, J. R., Kallemeyn, P. H., Keller, H. U., Kirk, R. L., Knudsen, J. M., Larsen, S., Lemmon, M. T., Madsen, M. B., Magalhães, J. A., Maki, J. N., Malin, M. C., Manning, R. M., Matijevic, J., McSween, H. Y., Moore, H. J., Murchie, S. L., Murphy, J. R., Parker, T. J., Rieder, R., Rivellini, T. P., Schofield, J. T., Seiff, A., Singer, R. B., Smith, P. H., Soderblom, L. A., Spencer, D. A., Stoker, C. R., Sullivan, R., Thomas, N., Thurman, S. W., Tomasko, M. G., Vaughan, R. M., Wänke, H., Ward, A. W. and Wilson, G. R. (1999). Overview of the Mars Pathfinder Mission: Launch through landing, surface operations, data sets, and science results . Space Science Reviews, E4. Source
    BibTeX
    @article{golombek1999overview,
      title = {Overview of the Mars Pathfinder Mission: Launch through landing, surface operations, data sets, and science results},
      author = {Golombek, Matthew P. and Anderson, R. C. and Barnes, J. R. and Bell, J. F. and Bridges, Nathan T. and Britt, Daniel T. and Brückner, J. and Cook, Richard A. and Crisp, D. and Crisp, Joy A. and Economou, T. and Folkner, W. M. and Greeley, R. and Haberle, R. M. and Hargraves, R. B. and Harris, J. A. and Haldemann, Albert F. C. and Herkenhoff, K. E. and Hviid, S. F. and Jaumann, Ralf and Johnson, Jeffrey R. and Kallemeyn, P. H. and Keller, Horst Uwe and Kirk, Randolph L. and Knudsen, J. M. and Larsen, S. and Lemmon, Mark T. and Madsen, M. B. and Magalhães, J. A. and Maki, Justin N. and Malin, Michal C. and Manning, Robert M. and Matijevic, J. and McSween, H. Y. and Moore, Henry J. and Murchie, Scott L. and Murphy, J. R. and Parker, Timothy J. and Rieder, R. and Rivellini, T. P. and Schofield, John T. and Seiff, A. and Singer, R. B. and Smith, Peter H. and Soderblom, L. A. and Spencer, David A. and Stoker, Carol R. and Sullivan, R. and Thomas, N. and Thurman, Sam W. and Tomasko, M. G. and Vaughan, R. M. and Wänke, H. and Ward, A. W. and Wilson, G. R.},
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      volume = {104},
      number = {E4},
      pages = {8523-8553},
      publisher = {American Geophysical Union (AGU)},
      year = {1999},
      doi = {10.1029/98je02554},
      abstract = {Mars Pathfinder successfully landed at Ares Vallis on July 4, 1997, deployed and navigated a small rover about 100 m clockwise around the lander, and collected data from three science instruments and ten technology experiments. The mission operated for three months and returned 2.3 Gbits of data, including over 16,500 lander and 550 rover images, 16 chemical analyses of rocks and soil, and 8.5 million individual temperature, pressure and wind measurements. Path‐finder is the best known location on Mars, having been clearly identified with respect to other features on the surface by correlating five prominent horizon features and two small craters in lander images with those in high‐resolution orbiter images and in inertial space from two‐way ranging and Doppler tracking. Tracking of the lander has fixed the spin pole of Mars, determined the precession rate since Viking 20 years ago, and indicates a polar moment of inertia, which constrains a central metallic core to be between 1300 and ∼2000 km in radius. Dark rocks appear to be high in silica and geochemically similar to anorogenic andesites; lighter rocks are richer in sulfur and lower in silica, consistent with being coated with various amounts of dust. Rover and lander images show rocks with a variety of morphologies, fabrics and textures, suggesting a variety of rock types are present. Rounded pebbles and cobbles on the surface as well as rounded bumps and pits on some rocks indicate these rocks may be conglomerates (although other explanations are also possible), which almost definitely require liquid water to form and a warmer and wetter past. Air‐borne dust is composed of composite silicate particles with a small fraction of a highly magnetic mineral, interpreted to be most likely maghemite; explanations suggest iron was dissolved from crustal materials during an active hydrologic cycle with maghemite freeze dried onto silicate dust grains. Remote sensing data at a scale of a kilometer or greater and an Earth analog correctly predicted a rocky plain safe for landing and roving with a variety of rocks deposited by catstrophic floods, which are relatively dust free. The surface appears to have changed little since it formed billions of years ago, with the exception that eolian activity may have deflated the surface by ∼3–7 cm, sculpted wind tails, collected sand into dunes, and eroded ventifacts (fluted and grooved rocks). Pathfinder found a dusty lower atmosphere, early morning water ice clouds, and morning near‐surface air temperatures that changed abruptly with time and height. Small scale vortices, interpreted to be dust devils, were observed repeatedly in the afternoon by the meteorology instruments and have been imaged.}
    }
  10. Malin, M. C., Ravine, M. A., Caplinger, M. A., Ghaemi, F. T., Schaffner, J. A., Maki, J. N., Bell III, J. F., Cameron, J. F., Dietrich, W. E., Edgett, K. S., Edwards, L., Garvin, J. B., Hallet, B., Herkenhoff, K. E., Heydari, E., Kah, L. C., Lemmon, M. T., Minitti, M. E., Olson, T., Parker, T. J., Rowland, S. K., Schieber, J., Sletten, R., Sullivan, R., Sumner, D. Y., Yingst, R. A., Duston, B., McNair, S. and Jensen, E. (2017). The Mars Science Laboratory (MSL) Mast cameras and Descent imager: I. Investigation and instrument descriptions . Earth and Space Science, 8. Source
    BibTeX
    @article{malin2017mars,
      title = {The Mars Science Laboratory (MSL) Mast cameras and Descent imager: I. Investigation and instrument descriptions},
      author = {Malin, Michal C. and Ravine, Michael A. and Caplinger, Michael A. and Ghaemi, F. Tony and Schaffner, Jacob A. and Maki, Justin N. and Bell III, James F. and Cameron, James F. and Dietrich, William E. and Edgett, Kenneth S. and Edwards, Laurence and Garvin, James B. and Hallet, B. and Herkenhoff, K. E. and Heydari, Ezat and Kah, Linda C. and Lemmon, Mark T. and Minitti, Michelle E. and Olson, T. and Parker, Timothy J. and Rowland, Scott K. and Schieber, Juergen and Sletten, Ron and Sullivan, R. and Sumner, Dawn Y. and Yingst, R. Aileen and Duston, Brian and McNair, Sean and Jensen, Elsa},
      journal = {Earth and Space Science},
      volume = {4},
      number = {8},
      pages = {506-539},
      publisher = {American Geophysical Union (AGU)},
      year = {2017},
      doi = {10.1002/2016ea000252},
      abstract = {Abstract The Mars Science Laboratory Mast camera and Descent Imager investigations were designed, built, and operated by Malin Space Science Systems of San Diego, CA. They share common electronics and focal plane designs but have different optics. There are two Mastcams of dissimilar focal length. The Mastcam‐34 has an f /8, 34 mm focal length lens, and the M‐100 an f /10, 100 mm focal length lens. The M‐34 field of view is about 20° × 15° with an instantaneous field of view (IFOV) of 218 μrad; the M‐100 field of view (FOV) is 6.8° × 5.1° with an IFOV of 74 μrad. The M‐34 can focus from 0.5 m to infinity, and the M‐100 from ~1.6 m to infinity. All three cameras can acquire color images through a Bayer color filter array, and the Mastcams can also acquire images through seven science filters. Images are ≤1600 pixels wide by 1200 pixels tall. The Mastcams, mounted on the ~2 m tall Remote Sensing Mast, have a 360° azimuth and ~180° elevation field of regard. Mars Descent Imager is fixed‐mounted to the bottom left front side of the rover at ~66 cm above the surface. Its fixed focus lens is in focus from ~2 m to infinity, but out of focus at 66 cm. The f /3 lens has a FOV of ~70° by 52° across and along the direction of motion, with an IFOV of 0.76 mrad. All cameras can acquire video at 4 frames/second for full frames or 720p HD at 6 fps. Images can be processed using lossy Joint Photographic Experts Group and predictive lossless compression.}
    }
  11. Girerd, A. R., Kuhn, S., Roth, B., Gaines, D., Scandore, S., Cummings, D., Mendoza, R., Lefland, M., Bareh, M., Siegfriedt, R., Lenda, M., Reich, K., Shah, B. and Bohannon, E. (2022). Cross-Cutting Flight Infrastructure Improvements on M2020 . IEEE Aerospace Conference. Source
    BibTeX
    @inproceedings{girerd2022cross,
      title = {Cross-Cutting Flight Infrastructure Improvements on M2020},
      author = {Girerd, Andre R and Kuhn, Stephen and Roth, Brian and Gaines, Dan and Scandore, Steve and Cummings, David and Mendoza, Ricardo and Lefland, Mallory and Bareh, Magdy and Siegfriedt, Rebekah and Lenda, Matthew and Reich, Kevin and Shah, Biren and Bohannon, Emily},
      booktitle = {IEEE Aerospace Conference},
      pages = {1-15},
      publisher = {IEEE},
      year = {2022},
      doi = {10.1109/aero53065.2022.9843523},
      abstract = {Mars2020 (M2020) was formulated as a mission that leveraged as much Mars Science Laboratory (MSL) heritage as possible, while focusing major new development efforts on the original and unique elements needed to accomplish the different mission objectives. Well publicized examples of high profile new developments include precision landing, the sampling and caching system, the specific instrument suite, improved mobility via Autonomous Navigation, and later the addition of the Ingenuity helicopter. Less well known are the refinements to the core flight infrastructure, primarily in the cross-cutting functions of Telecom, Avionics, Data Management, Communications Behaviors, and Parameter Management. These enhancements are introduced predominately via flight software, and represent increases in capability that justified their inclusion in an otherwise heritage-focused project environment. Perseverance's cross-cutting flight infrastructure improvements fall into and across the following five categories. First is a trimming of the software footprint of infrastructure modules, in order to make room for memory demands elsewhere in the system. Second is the minimization of data volume to be downlinked, through various methods such as the incorporation of new compression options. Third is the maximization of the available downlink bandwidth for data, by curtailing content-less data (fill) and introducing an improved UHF proximity link protocol. Fourth is a reduction in vulnerabilities, through increased file system redundancy, robustness, and software process monitoring. Fifth is an increase in operations efficiency by lowering file system mount times, improving parallelism between simultaneous events, minimizing the time to recover from file system errors, streamlining the purging of obsolete data, and reducing the number of commands to service parameters by a factor of 100. Individually, none of the cross-cutting infrastructure improvements are likely to garner headlines, but collectively they appreciably improve the safety and operability of Perseverance over its predecessor. This paper will describe the improvements, their promise, and where applicable, their actual impact in operations.}
    }