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Inertial Navigation Filters
This module contains implementations of various inertial navigation filters, including Kalman filters and particle filters. These filters are used to estimate the state of a strapdown inertial navigation system based on IMU measurements and other sensor data. The filters use the strapdown equations (provided by the StrapdownState) to propagate the state in the local level frame.
Currently, this module contains an implementation of a full-state Unscented Kalman Filter (UKF) and a full-state particle filter. For completeness, an Extended Kalman Filter (EKF) should be included, however, a strapdown EKF INS is typically implemented as an error state filter, which would require a slightly different architecture.
Contained in this module is also a simple standard position measurement model for both the UKF and particle filter. This model is used to update the state based on position measurements in the local level frame (i.e. a GPS fix).
Structs§
- GPSPosition
AndVelocity Measurement - GPS Position and Velocity measurement model
- GPSPosition
Measurement - GPS position measurement model
- GPSVelocity
Measurement - GPS Velocity measurement model
- Gravity
Anomaly Measurement - Magnetic
Anomaly Measurement - Particle
- Particle
Filter - Particle filter for strapdown inertial navigation
- Relative
Altitude Measurement - A relative relative altitude measurement derived from barometric pressure. Note that this measurement model is an altitude measurement derived from a barometric altimeter and not a direct calculation of altitude from the barometric pressure.
- Strapdown
Params - Basic strapdown state parameters for the UKF and particle filter initialization.
- UKF
- Strapdown Unscented Kalman Filter Inertial Navigation Filter
Traits§
- Measurement
Model - Generic measurement model trait for all filters