Housekeeping Data: Can You Afford Not to Compress It?

Abstract

Previous work at ESA/ESOC showed that spacecraft housekeeping telemetry contains significant amounts of information redundancy. A simple algorithm was proposed that removed this redundancy almost as effectively as well known commercial products like zip. However conventional wisdom says that even if stored housekeeping telemetry can be compressed -it should not be. At first glance the arguments appear reasonable; it would reduce the robustness of the ground space link, it would make using existing infrastructure more difficult, it would be complicated to implement as on-board software or too resource hungry. Finally there is the old argument that as housekeeping telemetry is typically only a fraction of the total mission data it would not be worth compressing. In this paper we intent to turn that conventional wisdom on its head as we make the move from theory to reality. We test our algorithm across a variety of mission types, solve the risk problem, propose an architecture that reuses existing infrastructure and implement the algorithm on real hardware using real data. Finally we show that there are additional advantages to using this compression technique besides freeing bandwidth and these can be even more significant than the obvious advantages. Can you afford not to compress housekeeping data? The results in this paper might change your answer. Nomenclature AOCS= Attitude and Orbit Control System CCSDS = Consultative Committee for Space Data Systems ESA = European Space Agency FER = Frame Error Rate HKTM = House-keeping Telemetry OBSW = On-board software PUS = Packet Utilization Standard RLE = Run Length Encoding SLE = Space Link Extension

Resiliency and Efficiency of the CCSDS 124.0-B-1 Telemetry Compression Standard

“…In [6], bitwise exclusive-or (XOR) operations are applied periodically within the group, and then a modified version of run-length encoding (RLE) is proposed to encode the resulting data. In [1], [3], it is shown that lossless compression methods such as Lempel-Ziv (LZ) and RLE yield significantly better compression results when applied to individual bit positions across several data packets. In [4], groups are dynamically created based on a similarity metric, and then the differences between consecutive packets in a group are coded with either RLE or LZ.…”

“…This is analogous to [8], which interleaves the transmission of packet differences and full packet contents. In terms of resiliency to data loss events -but not realtime transmission capabilities-, periodically transmitting full reference packets is roughly equivalent to [1], [3], [4], [6], [17], [18] when packets are divided in groups and compressed separately. The effect on compression efficiency of periodically activating both the full mask and uncompressed flags is analyzed in Section IV-D.…”

“…Housekeeping telemetry is defined as the data fraction produced on board space and remote sensing systems for the purpose of monitoring their correct functioning. These data are usually composed of values periodically registered by different types of sensors, including temperature, pressure, attitude, and orbit control measurements [1]. Reliable and timely reception of these data is paramount to guarantee nominal system behavior, as well as its safety and that of surrounding spacecraft [2].…”

“…It is worth noting that data loss events may happen even in the presence of strong forward error correction mechanisms at the data link layer, e.g., those described in [11]- [15]. Although most space links are designed to offer frame error rates between 10 −7 and 10 −5 , data losses do occur in practice due to low elevations, very bad weather, operator errors and intermittent contact during contingency situations such as safe mode [1], [13]. Thus, it is necessary to employ algorithms that allow the decompression of incomplete compressed data streams.…”