Abstract
For many tracking applications, the measurement errors onsuccessive observations are correlated. Using a first-order Markov model for the correlation, we present analytical expressions for the time-varying covariance and gains of an alpha-beta tracking filter.To a good approximation, the effect of correlation is to increase the time interval between measurements by a factor (1+a)/(1-a),where a is the coefficient of correlation between successive measurements.

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