Abstract :
Passive tracking relies on detection of energy emitted by zero or more targets in surveillance space. When detection occurs, the angle of arrival, or the angle between the sensor and the possible target is measured, with a measurement error. Both targets and sensors can be moving, thus additional source of error is the sensor position uncertainty. If the targets emit beams of energy randomly, then each sensor will detect each target at random times, which are independent from sensor to sensor. False detections or clutter measurements also occur at random times for each sensor. Existence, number, and position of targets are unknown in the surveillance region. The origin of each measurement is unknown, as the measurement may be a detection from any target being tracked, or a clutter detection, or a detection from a new target. The recursive algorithm presented integrates information from measurements received by an arbitrary number of sensors, to determine the existence, number, and position of targets in a stochastic manner, given assumptions listed above. Simulations show the effectiveness of this approach in a multi-target scenario.
Keywords :
"Target tracking","Radar tracking","Surveillance","Clutter","Current measurement","Sonar detection","Radar detection","Filters","Object detection","Coordinate measuring machines"