The use of mobile sensor networks for multi-target tracking is an active research field. This paper describes the application of a novel two-layer relaxation for high-level control and coordination of UAVs to optimally track a set of moving targets considering a limited resources scenario. Using a singlebest tracking criterion, the scheme deploys distributed algorithms constrained to ensure ful...

In multi-object stochastic systems, the issue of sensor management is a theoretically and computationally challenging problem. In this paper, we present a novel random finite set (RFS) approach to the multi-target sensor management problem within the partially observed Markov decision process (POMDP) framework. The multi-target state is modelled as a multi-Bernoulli RFS, and the multi-Bernoulli...

The passive direction finding cross localization method is widely adopted in passive tracking, therefore there will exist masses of false intersection points. Eliminating these false intersection points correctly and quickly is a key technique in passive localization. A new method is proposed for passive locating and tracking multi-jammer target in this paper. It not only solves the difficulty ...

To maintain custody of the increasing number of detectable objects in Earth orbit, tracking systems require robust methods of multi-target state estimation and prediction. One alternative to the classic multiple hypothesis and probabilistic data association methods uses a random finite set for modeling the multi-target state. The common forms of such filters sacrifice knowledge of specific targ...

Non-intrusive video-detection for traffic flow observation and surveillance is the primary alternative to conventional inductive loop detectors. Video Image Detection Systems (VIDS) can derive traffic parameters by means of image processing and pattern recognition methods. Existing VIDS emulate the inductive loops. We propose a trajectory based recognition algorithm to expand the common approac...

The tracking performance of JPDA-based algorithms will be decreased with the increase of sensors amount and clutter density. Thus it is necessary to find out a multi-sensor data fusion tracking algorithm which has lower computation and higher tracking accuracy. Since the motion direction of the targer is viewed as a key factor in data correlation, the pseudodirection tracking gate can be improv...

The problem of tracking multiple targets with passive bearings-only measurements is extremely challenging and rarely addressed explicitly in the literature. The difficulty arises mainly due to the low information content and non-linearity of the received measurements. Furthermore, effects such as high clutter density, closely spaced targets, and crossing targets are commonplace in passive track...

In multi-sensor target tracking systems, measurements from the same target can arrive out of sequence, called the out-of-sequence measurements (OOSMs). The resulting problem – how to update the current state estimates with the “old” measurements – has been solved optimally and sub-optimally for onelag as well as multi-lag OOSM update. In general, the existing algorithms assume perfect target de...

Sensors provide a key feedback link allowing robotic and autonomous systems to react to their environments. Without this feedback, robotic and autonomous systems will operate in an uncontrolled manner, since they don’t have the ability to perceive and respond to their environments. The limited capabilities of static sensors especially in complex applications and environments force the use of mu...