GNSS Receiver Motion Parameter Estimation via Closed-Loop Filtering
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Solution Overview
Problem
Existing methods for determining motion parameters of GNSS receivers, such as GPS and GLONASS, face challenges in accurately estimating full increments of coordinates, velocity vector projections, and acceleration vector due to noise and fluctuations in signal measurements.
Innovation Solution
The system employs closed-loop tracking filters of the 2nd or 3rd order, powered by unsmoothed full carrier phase estimates converted using the ordinary least squares method, to produce smoothed estimates of motion parameters by filtering out noise and fluctuations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If unsmoothed full carrier phase estimates are used directly for motion parameter estimation, then the response speed is fast, but the measurement precision deteriorates due to noise and fluctuations
Solution Approach 1:
A closed-loop tracking filter is introduced as an intermediary between the unsmoothed carrier phase estimates and the motion parameter estimation. The filter processes the noisy phase measurements to produce smoothed velocity and acceleration estimates, eliminating the need to choose between fast response and high precision.
2Measurement precision
If smoothing filters are applied to carrier phase estimates, then the measurement precision improves, but the device complexity increases
Solution Approach 1:
The patent transforms the carrier phase measurements into velocity and acceleration parameters through a closed-loop tracking filter. By changing the measurement parameters from position (phase) to motion parameters (velocity, acceleration), the system achieves smoothing and noise reduction while maintaining computational efficiency.
3Device complexity
If conventional Doppler offset measurement methods are used, then the device complexity is low, but the measurement precision of motion parameters deteriorates
Solution Approach 1:
The closed-loop tracking filter employs feedback mechanisms where the estimated motion parameters are continuously refined based on the difference between measured and predicted carrier phase values. This feedback process improves measurement precision without requiring complex additional hardware.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach enables high-accuracy estimation of motion parameters, including smoothed coordinate increments, velocity vector projections, and acceleration vectors, enhancing the precision of GNSS receiver positioning and navigation.
Implementation Method 1
The system includes a PLL that tracks the changing signal frequency and outputs non-smoothed frequency estimates into a filter of frequency estimates (FFE)
Implementation Method 2
The FFE then smooths noise in the signal to produce a more accurate smoothed frequency estimate of the input signal
Implementation Method 3
a block of NCO full phase computation (OFPC)
Implementation Method 4
a block of signal phase primary estimation (SPPE) and a first type adaptive filter filtering the signal from the output of SPPE
Data Source
AI summary
A method and a receiver apparatus allows obtaining accurate estimates of motion parameters of a mobile receiver, including smoothed estimates of total coordinates increments relative to its initial position, projections of velocity vector and acceleration vector. High estimation accuracy is achieved by filtering the biased or unbiased estimates of total coordinate increments relative to the receiver's initial position using smoothing tracking filters of a 2-nd or 3-rd order.