access icon openaccess Improved converted measurement Kalman filter for satellite-borne multi-target tracking

This study introduces a special converted measurement Kalman filter (CMKF) algorithm which apply to satellite for tracking target. Typical CMKF applies to radar which measures targets in spherical coordinate system. The new algorithm can be used by satellite which measures target's latitude and longitude. Improved CMKF algorithm tracks target in simple situation but is not able to deal with multi-target and information missing situation. Multiple hypothesis tracking (MHT) can track multi-target accurately and has the ability to initial track and end track at all times. For satellite, MHT use improved CMKF to calculate cost matrix and update the state estimate and estimate covariance. In the simulation, tracking process is simulated by MATLAB. Single target measured by satellite can be tracked accurately by CMKF algorithm. MHT can track multi-target accurately and distinguish the information missing rightly.

Inspec keywords: state estimation; Kalman filters; target tracking

Other keywords: multiple hypothesis tracking; spherical coordinate system; typical CMKF; initial track; single target; information missing situation; tracking target; special converted measurement Kalman filter algorithm; improved CMKF algorithm tracks target; satellite-borne multitarget tracking; end track

Subjects: Radar equipment, systems and applications; Filtering methods in signal processing; Optical, image and video signal processing

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http://iet.metastore.ingenta.com/content/journals/10.1049/joe.2019.0207
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