Prefiltration in Kalman filter with a priori indeterminacy
Abstract
A stable nonlinear discrete Kalman filter is synthesized for measurement objects with a priori indeterminate, and variable, signal and noise distribution. A robust algorithm of prefiltration is used for obtaining stable maximumlikelihood estimates of the state of a dynamic system in the case of nonGaussian noise. The estimation problem is expressed in the form of a recurrence relation containing a positivedefinite symmetric matrix, whereupon the synthesis problem is formulated in terms of a system of corresponding difference equations in which the measurement errors have been converted to Gaussian ones.
 Publication:

USSR Rept Electron Elec Eng JPRS UEE
 Pub Date:
 January 1985
 Bibcode:
 1985RpEEE.......27S
 Keywords:

 Electromagnetic Noise;
 Kalman Filters;
 Nonlinear Filters;
 Algorithms;
 Difference Equations;
 Distribution (Property);
 Errors;
 Maximum Likelihood Estimates;
 Electronics and Electrical Engineering