Time Series Compression Using Dynamic Mask Packets
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Solution Overview
Problem
Existing methods for compressing spacecraft housekeeping telemetry data are not robust enough to operate in chain mode, require a-priori knowledge of the monitored system, and introduce complexity and overhead, especially when dealing with real-time data and packet loss.
Innovation Solution
A method that uses a dynamically updated mask packet to encode and decode time series data, allowing operation in chain mode with high compression efficiency, and includes change history data to reconstruct mask packets even with packet loss, eliminating the need for external synchronization and historical telemetry access.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If traditional compression algorithms are used on spacecraft housekeeping telemetry data, then bandwidth is saved, but the algorithms are not robust enough to operate in chain mode and require a-priori knowledge of the monitored system
Solution Approach 1:
The mask packet is dynamically updated based on change history data from previously decoded packets, allowing the compression algorithm to adapt to changing data patterns without requiring a-priori knowledge. This dynamic adaptation enables robust operation in chain mode where each packet stands independently.
Solution Approach 2:
Change history data is accumulated from previously decoded packets to predict future data patterns. This preliminary accumulation of historical information enables the algorithm to prepare appropriate mask packets in advance, improving compression efficiency without requiring external synchronization or a-priori system knowledge.
2Loss of information
If compression algorithms are implemented to increase information content in housekeeping telemetry, then more parameters can be sampled at higher frequencies, but system complexity and processing power requirements increase
Solution Approach 1:
The telemetry data is segmented into fixed-length packets with structured formats (header, data fields, checksum). This segmentation allows independent processing of each packet without requiring complex analysis of entire data streams, reducing processing complexity while maintaining high information content through efficient compression of individual packets.
Solution Approach 2:
The algorithm changes parameters dynamically by updating mask packets based on observed data patterns. Instead of using fixed compression parameters, the system adapts parameters like mask packet content and change history data based on actual telemetry characteristics, achieving high compression ratios without requiring complex pre-analysis of the monitored system.
3Loss of energy
If packet stores are compressed using normal compression algorithms, then bandwidth is reduced, but data mixing in generation and storage processes causes algorithms to expand rather than compress packet stores
Solution Approach 1:
The compression algorithm processes packets in a periodic sequence, maintaining a fixed packet structure with consistent formatting. Each packet follows the same periodic pattern of header-data-checksum organization, allowing the compression algorithm to work efficiently on regularly structured data without being disrupted by data mixing in storage processes.
Solution Approach 2:
All telemetry packets are formatted homogeneously with fixed lengths and consistent data types in standardized fields. This homogeneity eliminates the disruptive effects of data mixing during storage and retrieval, allowing compression algorithms to achieve consistent compression ratios rather than expanding data due to structural variability.
4Loss of energy
If real-time compression of housekeeping telemetry data is implemented, then bandwidth efficiency is improved, but modifications in the critical command and control chain are required which increases risk
Solution Approach 1:
The compression algorithm is self-sufficient, using only information contained within the packet stream itself (change history from previously decoded packets) to perform compression. It does not require external synchronization signals, a-priori system knowledge, or modifications to the command and control chain, thereby achieving real-time compression without increasing mission risk.
Solution Approach 2:
The mask packet acts as an intermediary that bridges the compressed data and the original telemetry format. It contains prediction information derived from change history data, enabling the decompression process to reconstruct original packets accurately without requiring modifications to existing command and control systems.
5Ease of operation
If a fixed mask packet is used for compression, then processing is simpler, but compression efficiency decreases when data patterns change
Solution Approach 1:
The mask packet transitions from a fixed structure to a dynamic one that updates based on change history data from previously decoded packets. This dynamic adaptation allows the compression algorithm to maintain simplicity in processing while significantly improving compression efficiency by adapting to changing data patterns in the telemetry stream.
Data Source
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AI summary
The method comprises receiving a plurality of data packets of time series data and sequentially encoding the plurality of data packets. Sequentially encoding the plurality of data packets comprises, for a data packet among the plurality of data packets, obtaining a reference data packet for the data packet, obtaining a mask packet indicative of which of the bits in the data packet are predictable and which of the bits in the data packet are not predictable obtaining change history data indicative of previously changed bits of the mask packet, determining an updated mask packet based on the mask packet, the data packet, and the reference data packet, determining updated change history data based on the change history data, the mask packet, and the updated mask packet, determining, as unpredictable bits, all those bits of the data packet that are indicated as not predictable by the updated mask packet, and generating an encoded data packet including a representation of the updated change history data and a representation of values of the unpredictable bits of the data packet.