Adaptive Compression for GNSS Digital Signal Samples
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Solution Overview
Problem
GNSS receivers in portable devices face challenges in minimizing memory and communication bandwidth requirements for digital signal samples, which are resource-intensive and power-consuming, especially when processing satellite navigational signals.
Innovation Solution
The implementation of signal pre-coding to reduce the size of digital signal samples before storage and transmission, using compression algorithms like Huffman coding, and adaptive methods to adjust compression parameters based on signal conditions, allowing for efficient processing and reducing memory and bandwidth needs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If digital signal samples are stored in memory for GNSS processing, then navigation and timing solutions can be generated, but memory size and power consumption increase
Solution Approach 1:
The patent extracts only the essential information from the full digital signal samples by identifying and retaining only the sign bit and magnitude bits that carry meaningful navigation data. This extraction process removes redundant information while preserving the core signal characteristics needed for correlation processing and navigation solution generation.
Solution Approach 2:
The patent applies different processing treatments to different parts of the signal sample. The sign bit is preserved separately to maintain signal polarity information, while the magnitude bits are quantized to a reduced number of bits. This local differentiation allows optimal compression of each component based on its information content and importance for navigation processing.
2Adaptability or versatility
If digital signal samples are transmitted over communication channel, then remote processing is enabled, but communication bandwidth requirements increase
Solution Approach 1:
The patent extracts and transmits only the essential signal characteristics by separating the sign bit from the magnitude bits and transmitting them with reduced precision. This extraction enables remote processing capabilities while significantly reducing the amount of data that must be communicated over the channel.
Solution Approach 2:
The patent changes the precision parameters of the transmitted signal data by reducing the number of bits used to represent magnitude information while maintaining the sign bit separately. This parameter modification allows the same navigation processing to be performed remotely with much lower bandwidth requirements.
3Measurement precision
If full precision digital samples are processed, then processing accuracy is maintained, but power consumption and computational load increase
Solution Approach 1:
The patent extracts only the critical information elements from full-precision samples - specifically the sign bit and essential magnitude information - thereby reducing the computational burden of processing while maintaining the precision needed for accurate correlation and navigation solution generation.
Solution Approach 2:
The patent applies different precision levels to different components of the signal sample locally. The sign bit is maintained with full precision (1 bit) to preserve signal polarity information critical for correlation, while the magnitude bits are reduced in precision. This local quality differentiation maintains overall processing accuracy while significantly reducing power consumption.
Data Source
AI summary
A method, apparatus, and system for reducing memory and communication bandwidth requirements for digital signal samples in Global Navigational Satellite System (GNSS) receivers using an adaptive compression/decompression process are described.