Title :
Track monitoring when tracking with multiple 2D passive sensors
Author_Institution :
IBM Corp., Boulder, CO, USA
fDate :
11/1/1991 12:00:00 AM
Abstract :
A fast method of track monitoring is presented which determines what tracks are good and what tracks have had data association problems and should be eliminated. The philosophy of tracking in a dense target environment with limited central processing unit (CPU) time is to acquire the targets, track them with as simple a filter as will meet requirements, and monitor the tracks to determine if they are still tracking a target or are tracking incorrect returns and should be terminated. After termination the true targets are reacquired. However, it is difficult to determine from simple track monitoring the correct interpretation of a poor track. Poor tracks can be a result of a sensor failure, target maneuver, or incorrect data association. The author describes track monitoring and provides a solution to this dilemma when tracking with multiple two-dimensional passive sensors. The method is much faster than other monitoring methods.
Keywords :
Kalman filters; tracking systems; Kalman filters; data association; dense target environment; filter; limited central processing unit; multiple 2D passive sensors; multiple hypothesis tracking; target maneuver; track monitoring; Acceleration; Central Processing Unit; Condition monitoring; Equations; Filters; Laser sintering; Missiles; Monitoring; Optimal control; Sensor phenomena and characterization; Sensor systems; Target tracking;
Journal_Title :
Aerospace and Electronic Systems, IEEE Transactions on