Abstract
Networked multiple sensors are used to solve the problem of maneuvering target tracking. To avoid the linearization of nonlinear dynamic functions, and to obtain more accurate estimates for maneuvering targets, a novel adaptive information-weighted consensus filter for maneuvering target tracking is proposed. The pseudo measurement matrix is computed with unscented transform to utilize the information form of measurements, which is necessary for consensus iterations. To improve the maneuvering target tracking accuracy and get a unified estimation in each sensor node across the entire network, the adaptive current statistical model is exploited to update the estimate, and the information-weighted consensus protocol is applied among neighboring nodes for each dynamic model. Based on posterior probabilities of multiple models, the final estimate of each sensor is acquired with weighted combination of model-conditioned estimates. Experimental results illustrate the superior performance of the proposed algorithm with respect tracking accuracy and agreement of estimates in the whole network.
Highlights
The maneuvering target tracking problem has drawn immense attention for many years in areas such as aircraft surveillance, radar tracking, and road vehicle navigation [1,2]
Maneuvering target tracking has become a common situation in the military field, the research of which is of great significance
To improve the tracking effect and the agreement between sensors, distributed computing is based on a consensus protocol
Summary
The maneuvering target tracking problem has drawn immense attention for many years in areas such as aircraft surveillance, radar tracking, and road vehicle navigation [1,2]. Based on PF, Reference [11,12] performed a very similar study They both fused the information of multiple predefined models to obtain a more accurate result, and utilized PF to estimate the target. To solve the model uncertainty of the target by the input estimation technique, an adaptive particle filter for maneuvering target tracking [21] is proposed. An adaptive interacting multiple model algorithm based on information-weighted consensus (IMAM-UICF) is proposed. This algorithm further improves the estimation accuracy of tracking maneuvering target on the basis of IMAM, and the consensus filter is the key to the improvement.
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