Constant velocity state update
Update State for Constant-Velocity Motion
Update the state of two-dimensional constant-velocity motion for a time interval of one second.
state = [1;1;2;1]; state = constvel(state)
state = 4×1 2 1 3 1
Update State for Constant-Velocity Motion with Specified Time Step
Update the state of two-dimensional constant-velocity motion for a time interval of 1.5 seconds.
state = [1;1;2;1]; state = constvel(state,1.5)
state = 4×1 2.5000 1.0000 3.5000 1.0000
state — Kalman filter state
real-valued 2D-by-N matrix
Kalman filter state for constant-velocity motion, specified as a
real-valued 2D-by-N matrix.
D is the number of spatial degrees of freedom of
motion and N is the number states. The
state is expected to be Cartesian state. For each
spatial degree of motion, the state vector, as a column of the
state matrix, takes the form shown in this
|Spatial Dimensions||State Vector Structure|
x represents the
vx represents the
velocity in the x-direction. If the motion model is 1-D,
values along the y and z axes are
assumed to be zero. If the motion model is 2-D, values along the
z axis are assumed to be zero. Position coordinates
are in meters and velocity coordinates are in meters/sec.
w — State noise
scalar | real-valued D-by-N matrix
State noise, specified as a scalar or real-valued D-by-N matrix. D is the number of spatial degrees of freedom of motion and N is the number of state vectors. For example, D = 2 for the 2-D motion. If specified as a scalar, the scalar value is expanded to a D-by-N matrix.
For a two-dimensional constant-velocity process, the state transition matrix after a time step, T, is block diagonal as shown here.
The block for each spatial dimension is:
For each additional spatial dimension, add an identical block.
C/C++ Code Generation
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Introduced in R2018b