Integrated GPS INS Navigation Using Extended Kalman Filter
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Solution Overview
Problem
Conventional satellite navigation systems face challenges in achieving accurate absolute earth relative navigation due to limitations in processing all available GPS data, particularly with the exclusion of accumulated carrier phase measurements, which are crucial for precise kinematic solutions.
Innovation Solution
An integrated GPS/INS navigation system that combines L1 pseudorange, L2 pseudorange, L1 accumulated carrier phase, and L2 accumulated carrier phase measurements with inertial data using an extended Kalman filter, optimizing navigation solutions by accounting for various error sources and incorporating inertial data to correct navigation paths.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional satellite navigation systems process only L1 pseudorange and L1 delta range signals, then the system complexity is reduced, but the navigation accuracy deteriorates due to exclusion of accumulated carrier phase measurements
Solution Approach 1:
The patent combines multiple previously separate processing streams (L1 pseudorange, L2 pseudorange, L1 accumulated carrier phase, and L2 accumulated carrier phase measurements) into a unified navigation solution framework. This merging allows all available measurement types to contribute simultaneously to the final navigation solution, resolving the contradiction by integrating diverse data sources rather than processing them separately or excluding some.
Solution Approach 2:
The patent creates a universal processing framework that handles multiple types of GPS measurements (pseudorange and accumulated carrier phase on both L1 and L2 frequencies) through a single integrated algorithm. This multi-functional approach allows the system to process diverse measurement types uniformly, improving navigation accuracy without proportionally increasing system complexity.
2Measurement precision
If an extended Kalman filter processes all available GPS data including L2 pseudorange and accumulated carrier phase measurements, then the navigation solution accuracy is improved, but the computational load increases
Solution Approach 1:
The patent applies preliminary ionospheric correction to L2 pseudorange measurements before they are fed into the extended Kalman filter. This pre-processing step reduces the computational burden on the filter by providing corrected input data, thereby improving navigation solution accuracy without proportionally increasing the computational energy required during the filtering process.
Solution Approach 2:
The patent transforms L2 pseudorange measurements by applying ionospheric correction parameters before processing. This parameter transformation converts raw L2 measurements into corrected values that are more suitable for navigation solution computation, improving accuracy while managing computational requirements through efficient parameter-based correction rather than more intensive processing.
3Ease of operation
If accumulated carrier phase measurements are excluded from processing, then the system operation is simplified, but the kinematic navigation accuracy deteriorates
Solution Approach 1:
The patent merges accumulated carrier phase measurements with pseudorange measurements in a unified processing framework. By combining these different measurement types rather than treating them separately or excluding carrier phase data, the system achieves improved kinematic navigation accuracy while maintaining operational simplicity through integrated processing.
Data Source
AI summary
A navigation system comprises at least one processor, a satellite navigation receiver operatively coupled to the processor and configured to receive a plurality of navigation signals from one or more navigation satellites, and an inertial measurement unit operatively coupled to the processor and configured to generate inertial measurement data. An extended Kalman filter is configured to receive the plurality of navigation signals and the inertial measurement data. A processor readable storage medium includes instructions executable by the processor to combine the plurality of satellite signals with the inertial measurement data in the extended Kalman filter to generate a navigation solution. The plurality of navigation signals includes L1 pseudorange measurements, L2 pseudorange measurements, L1 accumulated carrier phase measurements, and L2 accumulated carrier phase measurements.