Pdf An Adaptive Interacting Multiple Model Algorithm For Maneuvering

Pdf An Adaptive Interacting Multiple Model Algorithm For Maneuvering Currently, there are two main directions for the modeling of maneuvering targets, one is the single model algorithm, and the other is the multi model algorithm. Pdf | on jan 1, 2017, shu liang wang and others published an adaptive interacting multiple model algorithm for maneuvering targets tracking | find, read and cite all the research.

Pdf Maneuvering Target Tracking Based On An Adaptive Variable This paper proposes an improved interacting multi model (imm) tracking algorithm based on the adaptive markov transition probability matrix, which can be utilized in ra dar systems for high speed…. 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. In this paper, 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. An adaptive interacting multiple model algorithm (aimm) is presented in this paper to track a maneuvering target. each model is assigned a fixed deterministic acceleration to cope with the different target accelerations.

Pdf Adaptive Estimation Using Interacting Multiple Model With Moving In this paper, 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. An adaptive interacting multiple model algorithm (aimm) is presented in this paper to track a maneuvering target. each model is assigned a fixed deterministic acceleration to cope with the different target accelerations. 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. Critical to limiting algorithm computations while achieving the desired tracking performance. this requirement is achieved with the interacting multiple model (imm) algorithm.1 the imm algorithm is a method for combining state hypotheses. A nonlinear tracking solution for maneuvering aerial targets based on an adaptive interacting multiple model (imm) framework and unscented kalman filters (ukfs), termed as aimm ukf, to obtain more accurate estimates, better consistency of the tracker, and more robust prediction during sensor outages. 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.