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

Abstract

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.

Keywords

• target tracking
• state estimation
• Kalman filters
• satellite-borne multitarget tracking
• special converted measurement Kalman filter algorithm
• tracking target
• typical CMKF
• spherical coordinate system
• improved CMKF algorithm tracks target
• information missing situation
• multiple hypothesis tracking
• initial track
• end track
• single target