AUV Positioning Delay Compensation Using Doppler Kalman Filtering
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Underwater communication delays in Autonomous Underwater Vehicles (AUVs) cause positioning errors due to data transmission delays, affecting navigation accuracy and safety.
Innovation Solution
A communication delay compensation method using Doppler measurement information to reconstruct the extended Kalman filter measurement equation, incorporating the included angle between the AUV's direction and velocity vectors, to improve positioning accuracy by compensating for underwater communication delays.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional extended Kalman filtering method is used for underwater positioning, then the system complexity is low, but the positioning accuracy deteriorates due to communication delay
Solution Approach 1:
The patent applies preliminary action by predicting the AUV position at the current time based on historical position information and velocity data before the delayed measurement data arrives. The extended Kalman filter uses the state equation to predict position forward in time, compensating for the delay effect. This allows the system to use earlier measurement data while achieving current time positioning accuracy.
Solution Approach 2:
The patent transforms the measurement equation parameters by introducing the included angle between the AUV direction vector and velocity vector. This parameter transformation allows the filter to work with delayed position data while predicting current position, effectively changing the temporal parameter relationship between measurement and prediction to resolve the accuracy-due-to-delay problem.
2Measurement precision
If communication delay compensation is implemented using extended Kalman filter with Doppler measurement, then the positioning accuracy is improved, but the algorithm complexity increases
Solution Approach 1:
The patent segments the positioning problem into two distinct parts: prediction (using state equation with velocity and direction) and update (using Doppler measurement and included angle). This segmentation allows the complex compensation task to be divided into manageable computational steps, reducing overall algorithmic complexity while maintaining accuracy.
Solution Approach 2:
The extended Kalman filter implements feedback by continuously comparing predicted position with actual delayed measurements, then using the measurement residual to correct the predicted position. This feedback mechanism systematically reduces positioning error despite communication delays, improving accuracy through iterative correction.
3Loss of information
If data transmission is performed in underwater environment, then the navigation information can be obtained, but communication delay occurs affecting real-time navigation
Solution Approach 1:
The system performs preliminary position prediction using the state equation before the delayed navigation information arrives. By predicting position forward in time based on velocity and direction data, the system compensates for the time loss during transmission, ensuring real-time navigation capability despite communication delays.
Solution Approach 2:
Instead of waiting for current position data to arrive (forward time approach), the patent inverts the approach by predicting future position based on historical data and then adjusting with arrived measurements. This time-inversion strategy effectively compensates for transmission delay, transforming a time-loss problem into a solvable prediction-correction problem.
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
The method effectively reduces positioning errors caused by underwater communication delays, enhancing navigation accuracy and performance beyond conventional extended Kalman filtering methods.
Implementation Method 1
Doppler measurement information is substituted into a measurement equation to perform measurement update through direction angle information formed by a Doppler-measured direction vector
Data Source
AI summary
The disclosure provides a communication delay compensation method and a communication delay compensation system based on an autonomous robot, where the method includes the following steps: establishing a state equation based on a system model of an the AUV positioning system; acquiring an included angle between a direction vector of the AUV to an observation station and a velocity vector of the AUV based on the system model; establishing an observation equation according to the state equation and the included angle; establishing an extended Kalman filter equation based on the system model, the included angle and the observation equation; and calculating a position information predicted value at the current time by using the extended Kalman filter equation to complete communication delay compensation.