7.1 Acoustic positioning systems

Acoustic positioning systems are crucial for underwater navigation, using sound waves to determine a vehicle's location relative to reference points. These systems measure signal travel times between the target and beacons, employing trilateration or multilateration to calculate positions with varying degrees of accuracy and range.

Long Baseline (LBL), Short Baseline (SBL), and Ultra-Short Baseline (USBL) systems offer different trade-offs between accuracy, range, and ease of deployment. Each system has its strengths and limitations, making them suitable for various underwater applications depending on specific requirements and environmental conditions.

Acoustic Positioning Systems

Principles of Acoustic Positioning

Top images from around the web for Principles of Acoustic Positioning

• 

  Underwater acoustic positioning system - Wikipedia View original

  Is this image relevant?

• 

  Frontiers | Underwater Localization and Mapping Based on Multi-Beam Forward Looking Sonar View original

  Is this image relevant?

• 

  Underwater acoustic positioning system - Wikipedia View original

  Is this image relevant?

• 

  Frontiers | Underwater Localization and Mapping Based on Multi-Beam Forward Looking Sonar View original

  Is this image relevant?

1 of 2

Top images from around the web for Principles of Acoustic Positioning

• 

  Underwater acoustic positioning system - Wikipedia View original

  Is this image relevant?

• 

  Frontiers | Underwater Localization and Mapping Based on Multi-Beam Forward Looking Sonar View original

  Is this image relevant?

• 

  Underwater acoustic positioning system - Wikipedia View original

  Is this image relevant?

• 

  Frontiers | Underwater Localization and Mapping Based on Multi-Beam Forward Looking Sonar View original

  Is this image relevant?

1 of 2

• Acoustic positioning systems use sound waves to determine the position of an underwater object or vehicle relative to a reference point or baseline
• The basic principle involves measuring the time of flight (TOF) of acoustic signals between the target object and reference beacons with known positions
• Acoustic signals propagate through water at a speed of approximately 1500 m/s, which is affected by factors such as temperature, salinity, and pressure
• Trilateration or multilateration techniques are used to calculate the target's position by combining range measurements from multiple beacons
  • Trilateration uses the intersection of three spheres, each centered on a beacon, to determine the target's 3D position
  • Multilateration extends this concept to more than three beacons for improved accuracy and redundancy

Factors Affecting Acoustic Positioning Accuracy

• Acoustic positioning systems require precise synchronization between the target and reference beacons to accurately measure signal travel times
  • Clock drift and variable signal processing delays can introduce errors in TOF measurements
  • Techniques such as two-way ranging or time synchronization protocols (PTP, NTP) are used to mitigate these errors
• The accuracy of acoustic positioning depends on factors such as the frequency of the acoustic signals, the spacing of reference beacons, and environmental conditions
  • Higher frequency signals provide better ranging accuracy but have shorter range due to increased attenuation
  • Larger beacon spacing improves positioning accuracy but requires a larger deployment area
  • Environmental factors like temperature gradients, salinity variations, and multipath propagation can degrade positioning performance

LBL, SBL, and USBL Systems

Long Baseline (LBL) Systems

• Long baseline (LBL) systems use a network of transponders deployed on the seafloor, forming a large baseline array for positioning
• LBL systems offer high accuracy over large areas but require significant setup time and effort to deploy and calibrate the transponder network
• The target vehicle interrogates the transponders sequentially, and the round-trip travel times are used to calculate its position
  • The vehicle sends an acoustic signal to each transponder, which responds with a reply signal
  • The round-trip travel times are measured and converted to ranges using the known speed of sound in water
• LBL systems are commonly used for high-precision applications such as seafloor mapping, subsea construction, and long-term monitoring

Short Baseline (SBL) Systems

• Short baseline (SBL) systems use a smaller array of transponders mounted on a surface vessel or fixed platform
• SBL systems have a shorter range and lower accuracy compared to LBL but are easier to deploy and maintain
• The target vehicle's position is determined relative to the surface vessel or platform using trilateration
  • The transponders on the vessel or platform act as reference points for positioning
  • The vehicle's position is calculated based on the ranges measured from each transponder
• SBL systems are suitable for applications where the vehicle operates in close proximity to the surface vessel (ROV operations)

Ultra-Short Baseline (USBL) Systems

• Ultra-short baseline (USBL) systems use a single transceiver array mounted on a surface vessel or underwater vehicle
• USBL systems measure the range and bearing of the target relative to the transceiver array using phase-difference or time-difference of arrival techniques
  • The transceiver array consists of multiple elements that enable direction finding based on the phase or time differences of the received signals
  • The range is determined by measuring the round-trip travel time of the acoustic signal between the transceiver and the target
• USBL offers a compact and mobile solution for underwater positioning but has limited range and accuracy compared to LBL and SBL systems
  • USBL systems are commonly used for tracking AUVs, ROVs, and divers in real-time
  • The positioning accuracy of USBL systems is typically in the order of 0.5-1% of the slant range

Advantages and Limitations of Techniques

Advantages and Limitations of LBL Systems

• LBL systems provide high accuracy (centimeter-level) and long-range positioning but require extensive infrastructure and setup
• LBL is suitable for large-scale, long-duration missions where precision is critical, such as seafloor mapping or subsea construction
• The need for transponder deployment and calibration limits the flexibility and mobility of LBL systems
  • Transponders need to be precisely positioned and surveyed before operation
  • Calibration procedures involve measuring the relative positions of the transponders and the speed of sound in the deployment area

Advantages and Limitations of SBL and USBL Systems

• SBL systems offer a balance between accuracy and ease of deployment, making them suitable for medium-range applications
• SBL provides better accuracy than USBL but requires careful placement and calibration of the transponder array on the surface vessel
• The positioning accuracy of SBL systems is affected by the size of the transponder array and the stability of the surface vessel
• USBL systems are compact, mobile, and easy to deploy, making them ideal for small-scale, short-duration missions
• USBL allows for real-time tracking of multiple targets using a single transceiver array
• The accuracy of USBL systems decreases with increasing range and is sensitive to multipath effects and acoustic shadows

General Limitations of Acoustic Positioning Systems

• Acoustic positioning systems are subject to limitations such as acoustic signal attenuation, multipath propagation, and interference from ambient noise sources
  • Signal attenuation limits the effective range of acoustic positioning systems
  • Multipath propagation caused by reflections from the surface, seafloor, or obstacles can introduce errors in range measurements
  • Ambient noise from sources like shipping traffic, marine life, or weather can mask the acoustic signals and degrade positioning performance
• The choice of acoustic positioning technique depends on factors such as the required accuracy, range, deployment constraints, and environmental conditions

Acoustic Positioning for Robot Navigation

Acoustic Positioning Algorithms

• Acoustic positioning algorithms involve estimating the robot's position and orientation (pose) based on range measurements from acoustic beacons
• The robot's state is typically represented using a state vector that includes its position (x, y, z) and orientation (roll, pitch, yaw) in a reference frame
• Range measurements from acoustic beacons are combined with the robot's motion model and sensor data (inertial measurements, depth) to estimate its pose
• Trilateration algorithms, such as the least-squares method or the extended Kalman filter (EKF), are used to solve for the robot's position given range measurements from multiple beacons
  • The least-squares method minimizes the sum of squared errors between the measured and predicted ranges to estimate the robot's position
  • The EKF recursively updates the robot's state estimate by combining predictions from the motion model with range measurements, taking into account their respective uncertainties

Challenges and Techniques in Acoustic Positioning

• Acoustic positioning algorithms need to handle challenges such as measurement noise, outliers, and beacon position uncertainties
• Robust estimation techniques, such as RANSAC (Random Sample Consensus) or M-estimators, can be used to mitigate the impact of outliers on the positioning solution
  • RANSAC iteratively estimates the robot's position using random subsets of range measurements and selects the solution with the highest consensus
  • M-estimators modify the least-squares cost function to reduce the influence of outliers on the position estimate
• Beacon position uncertainties can be addressed through simultaneous localization and mapping (SLAM) techniques that jointly estimate the robot's pose and the beacon positions
  • SLAM algorithms, such as the extended Kalman filter SLAM (EKF-SLAM) or particle filter SLAM, maintain a probabilistic representation of the robot's pose and the beacon positions
  • The robot's pose and beacon positions are updated incrementally as new range measurements are obtained, allowing for online refinement of the positioning solution
• The performance of acoustic positioning algorithms can be improved by incorporating additional sensors (Doppler velocity logs, pressure sensors) and using sensor fusion techniques to combine their measurements
  • Doppler velocity logs provide measurements of the robot's velocity relative to the water, which can be integrated to estimate its position
  • Pressure sensors measure the robot's depth, providing an additional constraint for the positioning solution
  • Sensor fusion techniques, such as the Kalman filter or particle filter, probabilistically combine measurements from multiple sensors to obtain a more accurate and robust position estimate

Implementation Considerations

• Implementing acoustic positioning algorithms requires careful consideration of factors such as the coordinate frame conventions, time synchronization, and communication protocols between the robot and the beacons
• Coordinate frame conventions define the relationship between the global reference frame (world frame) and the local frames of the robot and beacons
  • Transformations between frames are necessary to express measurements and estimates in a common reference frame
  • Proper definition and management of coordinate frames are essential for consistent and accurate positioning
• Time synchronization ensures that range measurements and sensor data are properly time-stamped and aligned for integration in the positioning algorithm
  • Techniques such as network time protocol (NTP) or pulse-per-second (PPS) signals can be used to synchronize clocks between the robot and beacons
  • Accurate time synchronization is crucial for correctly associating range measurements with the corresponding robot poses
• Communication protocols define the format and sequence of messages exchanged between the robot and beacons for ranging and data transmission
  • Protocols specify the structure of acoustic signals, the timing of interrogations and responses, and the encoding of range measurements and other data
  • Robust and efficient communication protocols are necessary to ensure reliable and timely exchange of information for real-time positioning