Multiple Pass Smoothing for Inertial Navigation Accuracy
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Solution Overview
Problem
Portable navigation systems using inertial sensors face challenges with accuracy degradation over time, especially in indoor environments where GNSS signals are weak and magnetometer-derived heading angles are unreliable due to interference from man-made structures.
Innovation Solution
The method employs multiple pass smoothing (MPS) techniques that involve forward and backward processing of motion sensor data, including gyroscope and accelerometer data, to enhance navigation solutions by combining interim navigation solutions and applying additional passes to improve accuracy, which can be used with various navigation technologies like PDR, INS, and GNSS, even in the absence of external aiding information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If inertial sensors are used for navigation, then continuous information is provided in indoor/outdoor environments, but accuracy degrades over time
Solution Approach 1:
The system performs a first forward pass processing to obtain preliminary navigation solutions before performing backward pass processing. This preliminary action allows the system to establish initial estimates that are then refined through subsequent backward and forward passes, improving overall accuracy while maintaining continuous navigation capability
Solution Approach 2:
The system implements multiple pass smoothing where backward pass results are fed back into forward pass processing, and forward pass results are used to refine backward pass solutions. This feedback mechanism continuously improves navigation accuracy by iteratively refining estimates using both past and future information
2Measurement precision
If magnetometers are used to correct heading errors, then heading information is provided, but reliability decreases in indoor/urban environments due to magnetic interference
Solution Approach 1:
The system extracts and removes magnetometer data from the navigation solution process in environments where magnetic interference is detected or expected. By taking out the unreliable magnetometer input, the system avoids incorporating erroneous heading information while maintaining navigation functionality through inertial sensors alone
Solution Approach 2:
The system dynamically changes the weighting parameters of different sensor inputs based on environmental conditions. When magnetic interference is present, the system reduces the weight of magnetometer data and increases the weight of inertial sensor data, adapting the navigation solution to maintain reliability in challenging environments
3Measurement precision
If GNSS is used to correct navigation errors, then absolute position information is provided, but reliability decreases in indoor environments due to weak signals
Solution Approach 1:
The system extracts and excludes GNSS data from the navigation solution when signal reliability is insufficient, such as in indoor environments. By removing unreliable GNSS inputs, the system prevents degradation of overall navigation accuracy while maintaining continuous operation through inertial and sensor fusion methods
Solution Approach 2:
The system dynamically adjusts the contribution of GNSS data to the navigation solution based on signal quality metrics. When GNSS signals are weak or unreliable, the system automatically reduces their weight in favor of more reliable sensor inputs, creating a adaptive navigation system that maintains performance across varying environmental conditions
4Measurement precision
If multiple pass smoothing is applied to enhance navigation solutions, then accuracy is improved, but computational complexity increases
Solution Approach 1:
The system segments the smoothing process into distinct forward and backward passes, each handling specific computational tasks. By dividing the complex multiple pass smoothing into manageable segments, the system improves navigation accuracy through iterative refinement while keeping each individual processing stage computationally tractable
Data Source
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AI summary
The navigation solution of a device may be enhanced by performing multiple pass smoothing. Forward and backward processing of the input data may be performed to derive interim navigation solutions. One or more quantities of the interim navigation solutions may be combined to smooth the quantities. At least one additional pass of forward and backward processing may then be performed using quantities of the navigation solution that were combined to enhance the interim navigation solutions. Next, at least one uncombined quantity of the navigation solution from the enhanced interim navigation solution is combined to provide an enhanced smoothed navigation solution. Additional passes may be performed to combine other quantities of the navigation solution as desired.