GNSS Signal Processing Using Partial Correlation and Doppler Compensation
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Solution Overview
Problem
Existing methods for processing digital signals from GNSS receivers require significant processing power, making them inefficient, especially for high phase resolutions, and are often reliant on dedicated hardware, which is costly and complex.
Innovation Solution
A method that simplifies the correlation process, allowing for processing on a general-purpose microprocessor, using a receiver with a simple front-end circuit and a base-band processor, which forms chip sums and uses step functions for Doppler compensation, reducing the need for extensive processing power and memory.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If every data value is multiplied separately with its corresponding correlation value and the products are added up, then measurement precision is improved, but processing power requirements increase significantly
Solution Approach 1:
The correlation process is segmented into partial correlations over Doppler intervals. Instead of computing one large correlation sum, the method divides the correlation interval into multiple partial correlation intervals, each processed separately. This segmentation allows for efficient computation while maintaining high phase resolution, as each partial correlation can be computed with reduced complexity and then combined to achieve the final high-precision result.
Solution Approach 2:
The invention transforms the correlation computation by introducing a frequency dimension through Doppler intervals. By organizing the correlation process in the frequency domain and using step functions approximating complex exponential functions, the method achieves high phase resolution without requiring exhaustive multiplication of every data value with every correlation value, thus reducing processing power requirements while maintaining measurement precision.
2Measurement precision
If high phase resolutions are achieved through detailed correlation processing, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The receiver design integrates multiple functions into a unified correlation processing system. The same correlation engine that computes partial correlations over Doppler intervals also handles Doppler compensation and phase resolution determination. This multi-functionality reduces device complexity by eliminating the need for separate dedicated hardware blocks for each function, while still achieving high phase resolution through the sophisticated correlation algorithm.
Solution Approach 2:
The invention extracts the essential correlation computation from complex dedicated hardware and implements it through a simplified processing pipeline using step functions and partial correlations. By taking out only the necessary computational elements and removing redundant hardware complexity, the system achieves high phase resolution with a simpler device architecture that can be implemented with fewer components.
3Speed
If dedicated hardware is used for signal processing, then processing speed is improved, but manufacturing cost increases
Solution Approach 1:
The invention uses software-based correlation processing that replicates the functionality of dedicated hardware through algorithmic computation. By copying the essential correlation operations into a software implementation running on a general-purpose processor, the system achieves sufficient processing speed for GNSS signal acquisition and tracking while dramatically reducing manufacturing costs, as software can be updated without hardware changes and requires less expensive components.
Solution Approach 2:
The method changes the computational parameters by using step functions to approximate complex exponential functions and by organizing correlations into partial correlations over discrete Doppler intervals. These parameter changes enable the correlation process to be efficiently implemented in software with adequate processing speed, making it feasible to use general-purpose processors instead of expensive dedicated hardware while maintaining acceptable performance for GNSS applications.
Data Source
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AI summary
Complex digital data values derived from a DSSS signal, in particular, a GNSS signal, are delivered to a general purpose microprocessor at a rate of 8MHz and chip sums over eight consecutive data values spaced by a sampling length (TS), each beginning with one of the data values as an initial value, formed and stored. For code removal, each of a series of chip sums covering a correlation interval of 1ms and each essentially coinciding with a chip interval of fixed chip length (TC), where a value of a basic function (bm) reflecting a PRN basic sequence of a satellite assumes a correlation value (Bm), is multiplied by the latter and the products added up over a partial correlation interval to form a partial correlation sum. The partial correlation interval is chosen in such a way that it essentially coincides with a corresponding Doppler interval having a Doppler length (TD) where a frequency function used for tentative Doppler shift compensation and represented by a step function (sine, cosine) is constant. The partial correlation sums are then each multiplied by the value assumed by the frequency function in the corresponding Doppler interval and the products added up to form a correlation sum.