GNSS PPE Backward Smoothing Using Delta Carrier Phase
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Solution Overview
Problem
Existing GNSS-based positioning systems face challenges in achieving accurate location estimates prior to convergence, requiring significant memory and processing resources, especially for low-cost devices, due to the need for buffering raw measurements and using a separate extended Kalman filter for backward smoothing.
Innovation Solution
Implementing quasi-real-time PPE backward smoothing using delta carrier phase (DCP) information to buffer and process delta positioning information between epochs, eliminating the need for raw measurement buffering and a separate EKF engine.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional backward smoothing using a separate EKF engine and raw measurement buffering is implemented, then location accuracy prior to convergence is improved, but memory requirements and processing resources increase significantly
Solution Approach 1:
The patent merges the backward smoothing function into the existing PPE engine, eliminating the need for a separate EKF engine. The PPE engine performs both forward processing and backward smoothing using a unified algorithm that processes delta carrier phase measurements and position change values, reducing overall system complexity while maintaining accuracy.
Solution Approach 2:
The patent extracts only the essential information needed for backward smoothing (delta carrier phase measurements and position change values) from the raw measurements, rather than buffering all raw measurement data. This extraction approach reduces memory requirements while preserving the necessary information for accurate location estimation before convergence.
2Measurement precision
If raw measurement buffering is used for backward smoothing, then location accuracy is improved, but memory requirements increase
Solution Approach 1:
The patent extracts only the essential information needed for backward smoothing (delta carrier phase measurements and position change values) from the raw measurements, rather than buffering all raw measurement data. This extraction approach reduces memory requirements while preserving the necessary information for accurate location estimation before convergence.
Solution Approach 2:
Instead of buffering all raw measurement data (excessive action), the patent buffers only the necessary delta carrier phase measurements and position change values (partial action). This selective buffering approach reduces memory consumption while maintaining sufficient information for accurate backward smoothing.
3Measurement precision
If a separate EKF engine is used for backward smoothing, then location accuracy is improved, but device complexity and processing requirements increase
Solution Approach 1:
The patent merges the backward smoothing function into the existing PPE engine, eliminating the need for a separate EKF engine. The PPE engine performs both forward processing and backward smoothing using a unified algorithm that processes delta carrier phase measurements and position change values, reducing overall system complexity while maintaining accuracy.
Solution Approach 2:
The PPE engine is designed to perform multiple functions: it conducts forward processing to generate initial position estimates and simultaneously performs backward smoothing using the same engine. This multi-functional design eliminates the need for separate processing engines and reduces overall system complexity.
4Measurement precision
If conventional backward smoothing methods are used, then location accuracy is improved, but processing time and latency increase
Solution Approach 1:
The patent performs preliminary computation of position change values and delta carrier phase measurements during the forward processing phase. By preparing this data in advance and storing it efficiently, the backward smoothing process can proceed more rapidly without requiring extensive real-time processing, thus reducing overall latency.
Data Source
AI summary
In some implementations, a global navigation satellite system (GNSS) device may determine a plurality of position estimates of the GNSS device for a plurality of epochs spanning a period of time beginning with a first epoch and ending with a second epoch. The GNSS device may determine position change values comprising a position change value of the GNSS device for each successive epoch of the plurality of epochs based at least in part on delta carrier phase (DCP) values for the plurality of epochs. The GNSS device may perform backward smoothing on the plurality of position estimates, modifying at least a portion of the plurality of position estimates based at least in part on the position estimate of the second epoch and the position change values. The GNSS device may output information indicative of at least a portion of the modified position estimates of the GNSS device.