Name
Abstract | ||
|---|---|---|
Passive Coherent Location (PCL) radar measures the bistatic parameters of a target: the time difference of arrival and the Doppler shift. In order to localize a target in the Cartesian coordinates, the data from multiple transmitter-receiver pairs can be used. This task is, however, challenging due to the ambiguities in the measurements assignment. In the paper, a tracking algorithm is presented, which decomposes the complicated task of target localization into two stages: tracking in the bistatic domain and tracking in the Cartesian domain. The bistatic tracker is used only for plot-to-plot association. The Cartesian tracker, based on the extended Kalman filter, uses the raw plots associated by the bistatic tracker to calculate the Cartesian parameters of the target. |
Year | Venue | Keywords |
|---|---|---|
2009 | Fusion | radar transmitters,passive radar,kalman filters,bistatic target parameter,passive coherent location,plot-to-plot association,passive coherent location radar,passive bistatic radar,doppler shift,target tracking,radar signal processing,time difference-of-arrival,radar receivers,radar tracking,extended kalman filter,time-of-arrival estimation,multiple transmitter-receiver,two-stage target tracking algorithm,cartesian coordinate,nonlinear filters,mathematical model,time measurement,data mining,time difference of arrival,covariance matrix,ellipsoids,transmitters |
Field | DocType | ISBN |
Radar,Computer vision,Doppler radar,Extended Kalman filter,Radar tracker,Computer science,Algorithm,Kalman filter,Bistatic radar,Artificial intelligence,Passive radar,Cartesian coordinate system | Conference | 978-0-9824-4380-4 |
Citations | PageRank | References |
10 | 1.23 | 0 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Mateusz Malanowski | 1 | 54 | 4.54 |
| Krzysztof S. Kulpa | 2 | 21 | 3.38 |
| Radoslaw Suchozebrski | 3 | 10 | 1.23 |