Reputation: 313
I have been trying to understand Kalman filter and how to use it. I am planning to write it in java.
I have real time location (longtitude, latitude) and speed data. I need to find the next location of a moving object. Locations are accurate there is no noise in the location data. The reason that I want to use Kalman filter is to estimate the next probable location of the object. I couldn't understand how to give the values to the matrices(Transition, Measurement,etc).
I need your help to create and understand structure of matrices. I am also open for the recommendations to the new algorithms.
Upvotes: 3
Views: 1729
Reputation: 755
You could take a look at some open-source implementations. The ASF provides the following:
The following code illustrates how to perform the predict/correct cycle:
for (;;) {
// predict the state estimate one time-step ahead
// optionally provide some control input
filter.predict();
// obtain measurement vector z
RealVector z = getMeasurement();
// correct the state estimate with the latest measurement
filter.correct(z);
double[] stateEstimate = filter.getStateEstimation();
// do something with it
}
Upvotes: 1