Time Series Compression Using Adaptive 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 are inefficient due to data mixing and real-time compression challenges, leading to suboptimal compression performance and increased system complexity.
Innovation Solution
A method that uses a dynamically updated mask packet to encode and decode time series data, allowing operation in chain mode with robustness against packet loss, eliminating the need for a-priori knowledge and simplifying ground software by using change history data to reconstruct mask packets and reduce CPU usage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If real-time compression of housekeeping telemetry data is implemented, then bandwidth saving and information content increase, but system complexity and mission risk increase due to modifications in the command and control chain
Solution Approach 1:
The compression algorithm operates autonomously on housekeeping data packets without requiring external control or synchronization. The algorithm self-adapts to data patterns and performs compression independently, eliminating the need for modifications in the command and control chain while achieving real-time compression of telemetry data
2Loss of information
If compression algorithms are applied to housekeeping data packets, then bandwidth is saved, but processing power requirements increase
Solution Approach 1:
The algorithm uses simple, computationally inexpensive operations that can be executed quickly with minimal processing power. By employing basic bitwise operations and straightforward compression techniques rather than complex algorithms, the solution achieves effective compression while consuming limited on-board processing resources
3Loss of information
If data packets are compressed to remove redundancy, then bandwidth efficiency improves, but compression performance deteriorates due to data mixing in generation and storage processes
Solution Approach 1:
The algorithm processes data packets in a segmented manner, handling each packet independently through systematic steps: identifying predictable bits, generating mask packets, creating change history data, and encoding only unpredictable bits. This segmentation approach effectively handles data mixing issues and achieves high compression ratios by focusing on actual data changes rather than entire mixed packets
4Productivity
If a-priori knowledge of the monitored system is used to optimize compression, then compression performance improves, but adaptability to different systems decreases
Solution Approach 1:
The algorithm is designed as a universal compression solution that works with any housekeeping telemetry data without requiring system-specific knowledge or configuration. It achieves this through automatic pattern recognition, adaptive mask generation, and universal data structures that accommodate different data types and formats, making it applicable across multiple spacecraft and system types
Data Source
AI summary
The method involves sequentially encoding the plurality of data packets, which involves, for a data packet, obtaining a reference 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.