Maneuvering Target Tracking via Smoothing and Filtering Through Measurement Concatenation

Measurement concatenation is a technique that takes advantage of the fact that typically measurements can be taken at a much higher rate than the algorithmic processing rate. The rapidly sampled measurements are stacked into a vector and related to the filter states at either the last or next algorithmic processing time. In this paper, a new innovations-based scheme of continuous maneuver estimation and filter adaptation is proposed. The main feature of the new algorithm consists of the combined use of smoothing and filtering, rendered possible due to measurement concatenation. Simulation results are presented to show the potential of the proposed method.

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