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Compute field intensity of tag acceleration and magnetometer data.

Source: R/check_AM.R
check_AM.Rd

Compute field intensity of acceleration and magnetometer data, and the inclination angle of the magnetic field. This is useful for checking the quality of a calibration, for detecting drift, and for validating the mapping of the sensor axes to the tag axes.

Usage

check_AM(A, M = NULL, fs = NULL, find_incl = TRUE)

Arguments

A

An accelerometer sensor structure or matrix with columns [ax ay az]. Acceleration can be in any consistent unit, e.g., g or m/s^2.

M

A magnetometer sensor structure or matrix, M=[mx,my,mz] in any consistent unit (e.g., in uT or Gauss).

fs

(optional) The sampling rate of the sensor data in Hz (samples per second). This is only needed if A and M are not sensor structures and filtering is required.

find_incl

(optional; logical) Should inclination be computed and returned? Default is TRUE.

Value

If find_incl is false, then the matrix fstr is returned. Otherwise, check_AM returns a list with elements:

  • fstr, The estimated field intensity of A and or M in the same units as A and M. fstr is a vector or a two column matrix. If only one type of data is input, fstr will be a column vector. If both A and M are input, fstr will have two columns with the field strength of A in the 1st column and the field strength of M in the 2nd column.

  • incl, The estimated field inclination angle (i.e., the angle with respect to the horizontal plane) in radians. incl is a column vector. By convention, a field vector pointing below the horizon has a positive inclination angle. This is only returned if the function is called with both A and M data.

Details

The sampling rate of fstr and incl is the same as the input sampling rate. This function automatically low-pass filters the data with a cut-off frequency of 5 Hz if the sampling rate is greater than 10 Hz. Frame: This function assumes a [north,east,up] navigation frame and a [forward,right,up] local frame.

Examples

AMcheck <- check_AM(
  A = matrix(c(-0.3, 0.52, 0.8), nrow = 1),
  M = matrix(c(22, -22, 14), nrow = 1),
  fs = 1
)