An interacting multiple model for multi-node target tracking algorithm was proposed based on a fuzzy neural network (FNN) to solve the multi-node target tracking problem of wireless sensor networks (WSNs). Measured error variance was adaptively adjusted during the multiple model interacting output stage using the difference between the theoretical and estimated values of the measured error cova...

Multi-target tracking systems typically provide sets of estimated target states as their output. It is challenging to be able integrate these outputs inputs other gain a better picture the area under surveillance since they do not conform standard observation model. Moreover, in cyclic distributed systems, there may common information between state estimates that would mean fused become overcon...

To evaluate multi-target video tracking results, one needs to quantify the accuracy of the estimated target-size and the Cardinality error as the well as measure the frequency of occurrence of ID changes. By surveying existing multi-target tracking performance scores and, after discussing their limitations, the work proposes three parameter-independent measures for evaluating multi target video...

The purpose of the effort reported here is to investigate modern multi-target tracking algorithms for high frequency active applications. High frequency active sensor systems are currently being evaluated by the Navy to meet the Sea Power 21 Sea Shield objectives for force protection and port security. These systems have elementary baseline tracking capabilities and could benefit from incorpora...