check_AM {tagtools}

Compute field intensity of tag acceleration and magnetometer data.

Description

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.

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.

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.

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
)