Paper
13 July 2000 Kalman filter vs. IMM estimator: when do we need the latter?
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Abstract
In this paper a performance comparison between a Kalman filter and the Interacting Multiple Model (IMM) estimator is carried out for single- target tracking. In a number of target tracking problems of various sizes, ranging from single-target tracking to tracking of about a thousand aircraft for Air Traffic Control, it has been shown that the IMM estimator performs significantly better than a Kalman filter. In spite of these studies and many others, the condition under which an IMM estimator is desirable over a single model Kalman filter has not been quantified. In this paper the limits of a single model Kalman filter vs. an IMM estimator are quantified in terms of the target maneuvering index, which is a f unction of target motion uncertainty, measurement uncertainty and sensor revisit interval. Naturally, the higher the maneuverability of the target (higher maneuvering index), the more the need for a versatile estimator like the IMM. Using simulation studies, it is shown that above a certain maneuvering index an IMM estimator is preferred over a Kalman filter to track the target motion. Performances of these two estimators are compared in terms of estimation errors and track continuity over the practical range of maneuvering indices. These limits should serve as a guideline in choosing the more versatile, but costlier, IMM estimator over a simpler Kalman filter.
© (2000) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Thiagalingam Kirubarajan and Yaakov Bar-Shalom "Kalman filter vs. IMM estimator: when do we need the latter?", Proc. SPIE 4048, Signal and Data Processing of Small Targets 2000, (13 July 2000); https://doi.org/10.1117/12.392013
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Cited by 11 scholarly publications.
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KEYWORDS
Filtering (signal processing)

Error analysis

Motion estimation

Motion models

Performance modeling

Motion measurement

Sensors

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