Gaussian mixture (GM) PHD filter
The gmphd
object is a filter that implements the
probability hypothesis density (PHD) using a mixture of Gaussian components. The filter
assumes the target states are Gaussian and represents these states using a mixture of Gaussian
components. You can use a gmphd
filter to track extended objects or
point targets. In tracking, a point object returns at most one detention per sensor scan, and
an extended object can return multiple detections per sensor scan.
You can directly create a gmphd
filter. You can also initialize a
gmphd
filter used with trackerPHD
by
specifying the FilterInitializationFcn
property of trackingSensorConfiguration
. You can use the provided initcvgmphd
, initctgmphd
, initcagmphd
, and initctrectgmphd
as
initialization functions. Or, you can create your own initialization functions.
creates a phd
= gmphdgmphd
filter with default property values.
allows
you to specify the states and corresponding state covariances of the Gaussian distribution
for each component in the density. phd
= gmphd(states,stateCovariances)states
and
stateCovariances
set the States
and StateCovariances
properties of the filter.
also allows you to specify properties for the filter using one or more name-value pairs.
Enclose each property name in quotes.phd
= gmphd(states,stateCovariances,Name,Value
)
predict | Predict probability hypothesis density of phd filter |
correctUndetected | Correct phd filter with no detection hypothesis |
correct | Correct phd filter with detections |
likelihood | Log-likelihood of association between detection cells and components in the density |
append | Append two phd filter objects |
merge | Merge components in the density of phd filter |
scale | Scale weights of components in the density |
prune | Prune the filter by removing selected components |
labeledDensity | Keep components with a given label ID |
extractState | Extract target state estimates from the phd filter |
clone | Create duplicate phd filter object |
[1] Vo, B. -T, and W. K. Ma. "The Gaussian mixture Probability Hypothesis Density Filter." IEEE Transactions on Signal Processing, Vol, 54, No, 11, pp. 4091–4104, 2006.
[2] Granstrom, Karl, Christian Lundquist, and Omut Orguner. "Extended target tracking using a Gaussian-mixture PHD filter." IEEE Transactions on Aerospace and Electronic Systems 48, no. 4 (2012): 3268-3286.
ggiwphd
| initcagmphd
| initctgmphd
| initctrectgmphd
| initcvgmphd
| partitionDetections
| trackerPHD
| trackingSensorConfiguration