A target tracking system using sensors of multiple modalities

Scheduling Multiple Sensors Using Particle Filters in Target Tracking

A critical component of a multi-sensor system is sensor scheduling to optimize system performance under constraints (e.g. power, bandwidth, and computation). In this paper, we apply particle filter sequential Monte Carlo methods to implement multiple sensor scheduling for target tracking. Under the constraint that only one sensor can be used at each time step, we select a sequence of sensor use...

Multiple Target Tracking With a 2-D Radar Using the JPDAF Algorithm and Combined Motion Model

Multiple target tracking (MTT) is taken into account as one of the most important topics in tracking targets with radars. In this paper, the MTT problem is used for estimating the position of multiple targets when a 2-D radar is employed to gather measurements. To do so, the Joint Probabilistic Data Association Filter (JPDAF) approach is applied to tracking the position of multiple targets. To ...

Multiple Target Tracking with Multiple Finite Resolution Sensors

In this paper tracking multiple targets with multiple finite-resolution sensors is presented with emphasis on the measurement-to-track association with possibly unresolved measurements. Two data association algorithms are considered. The multiple scan data association problem is first formulated as a multidimensional assignment problem with explicit new constraints for the unresolved measuremen...

Target Tracking by Using Seismic Sensors

Heterogeneous Multiple Sensors Joint Tracking of Maneuvering Target in Clutter

To solve the problem of tracking maneuvering airborne targets in the presence of clutter, an improved interacting multiple model probability data association algorithm (IMMPDA-MDCM) using radar/IR sensors fusion is proposed. Under the architecture of the proposed algorithm, the radar/IR centralized fusion tracking scheme of IMMPDA-MDCM is designed to guarantee the observability of the target st...