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The transition from the explicit mode to the implicit mode is performed locally and in a continuous fashion, providing a smooth hybrid explicit implicit calculation.
The structured hybrid system shows no remaining adhesion force after the topographic change and the smooth hybrid system drops to half of its former adhesive force.
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The next sections present the formulas for smoothed hybrid target state for any fixed lag N. The target trajectory state is composed of position and velocity components.
It creates a smooth, logical hybrid of iPad and "real" computer, in a way that the VNC apps do not.
The augmented state is also calculated for the EMM algorithm, and then fixed lag smoothing is used to obtain the smoothed target hybrid state at any scan.
This paper provides a new procedure to calculate the smoothed target hybrid state at fixed lag N. The benefits of the smoothing algorithm are compared for target tracking algorithms in the clutter using the HPRF radar.
The smoothed target hybrid state provides small estimation errors and produces excellent false track discrimination in the simulation conditions used in the proposed work.
The smoothing window can be of any length N. The proposed method to smooth the target hybrid state at fixed lag is also applied to the enhanced multiple model (EMM) tracking algorithm.
This paper presents a new method to smooth the target hybrid state at fixed lag N. It applies the proposed smoothing algorithm on both GMM-ITS and EMM algorithms to obtain the smoothing benefits for an HPRF radar.
This method smooths the target state at fixed lag N and considers all feasible multi-scan target existence sequences in the temporal window of scans in order to smooth the target hybrid state.
A new method to smooth the target hybrid state with Gaussian mixture measurement likelihood-integrated track splitting (GMM-ITS) in the presence of clutter for a high pulse repetition frequency (HPRF) radar is proposed.
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