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Event-triggered nonlinear state estimation with quantized innovations
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DOI：10.1016/j.jfranklin.2024.107339.png)
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Abstract
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This paper proposes an event-triggered (ET) estimator with quantization mechanism to relieve the bandwidth and energy limitations of wireless sensors, where the ET strategy reduces the overall communication rate of the system, and the quantization mechanism mitigates the instantaneous bit rate constraint. Then, Gaussian approximation is applied to derive the analytical form of the minimum mean squared error (MMSE) estimator under the event-triggered strategy and quantization mechanism. Furthermore, the relationship between the event-triggered parameter and the communication rate is explicitly established. Finally, theoretical results are validated through some simulations on a target tracking system.
Keywords:
Event-triggered communication
Communication rate
Quantized innovation
Unscented Kalman filter
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3.7
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6.2K
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1.5W
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