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We present an augmented continuous-discrete extended Kalman filter (EKF), capable of mitigating the effects of bad data and (random) measurement delay. We use an innovations-based Fisher-type scheme to identify and remove occurrences of corrupted sensor observations. We rely on time-stamp technology to accurately determine the duration of delay experience d by each received measurement packet. The...
The performance of a continuous-discrete Kalman filter using multi-sensor observations with irregular sampling patterns and/or delay in the measurement path is analyzed in terms of the associated error-covariance matrix. Such irregularities occur in geographically-distributed systems (such as the electric power grid) when observations are transmitted to an estimation/control center via an unreliable...
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