Aided Inertial Navigation System Toolbox - AINS


Description of Technology

Researchers at the University of Calgary have developed an aided inertial navigation system (AINSTM) toolbox as a set of libraries written for MatLab® software which can be called seperately. It also provides estimation tools to optimally combine the data files from an intertial measurement unit (IMU) together with information from other aiding sensors such as global positioning system (GPS), odometers, heading, and non-holonomic constraints.

Areas of Application
  • Land vehicle navigation applications
  • Direct georeferencing application for land and airborne mobile mapping applications (LiDar, aerial photography, etc.)
  • Pipeline mapping applications (Geo-pig, right-of-way mapping applications, etc.)
  • Pedestrian navigation applications
Competitive Advantages

The toolbox uses state-of-the-art strapdown integration and estimation techniques. The INS mechanization applies second-order coning and sculling corrections. Many options exist for the initial alignment. For tactical or navigation grade IMUs, the analytical coarse alignment and fine alignment techniques are implemented. In-motion alignment uses GPS-derived velocities for pitching and heading initialization. Levelling with user-given heading information can be used for the alignment of low-cost IMUs.

The following estimation techniques are implemented in the toolbox:

  • Linearized Kalman filter with feedback (extended Kalman filter)
  • Rauch-Tung-Striebel (RTS) smoother
  • Quaternion-based unscented Kalman filter
  • Backward unscented Kalman filter and smoother

The toolbox supports various attitude parameterizations including the direction cosine matrix (DCM), Euler angles, rotation vector, and quaternion. Tranformations between these parameterizations are also implemented. The following describes the functions of the toolbox:

  • INS alignment
    • Analytical coarse alignment
    • Fine alignment with zero velocity updates (ZUPTs) and the earth's rotation measurements
    • In-motion alignment using GPS-derived velocities
  • Roll and pitch from accelerometers and use given heading
  • Initiatlization with given attitude
  • INS Mechanization
  • Second order coning and sculling correction
  • Velocity integration
  • Position integration
  • Attitude integration
  • Extended Kalman Filter
  • 21 states incorporating errors in position, velocity, attitude, and sensors’ bias and scale factor
  • Coordinate update (from GPS or any other sources)
  • Navigation frame velocity update (from GPS or any other sources)
  • Vehicle frame velocity update (odometer and speedometer)
  • Zero velocity update (ZUPT)
  • Non-holonomic constraints
  • Heading update
  • RTS smoother yields best solution utilizing all the measurements of past, current, and future
  • Quaternion-based unscented Kalman filter and smoother
  • Changing Level Arm
    • In airborne survey applications, there may be changes in the lever arm from the GPS antenna to the IMU
    • This module allows the AINS™ Toolbox to account for these changes
    • Users can specify a file containing details on the lever arm changes
    • Particularly beneficial in applications where the GPS or INS platform is rotating, such as IFSAR airborne mapping systems