USE OF OPTIMAL ESTIMATION THEORY, IN PARTICULAR THE KALMAN FILTER, IN DATA-ANALYSIS AND SIGNAL-PROCESSING

[1] Gelb A, 1992, APPL OPTIMAL ESTIMAT

[2] Haykin S., 1986, ADAPTIVE FILTER THEO

[3] Kalman R.E., 1960, J BASIC ENG-T ASME, V82, P35, DOI [10.1115/1.3662552, DOI 10.1115/1.3662552]

[4] Kalman RE., 1961, T ASME D, V83, P95, DOI [DOI 10.1115/1.3658902, 10.1115/1.3658902]

[5] A DIRECT APPROACH TO IDENTIFY THE NOISE COVARIANCES OF KALMAN FILTERING [J]. IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 1980, 25 (04) : 841 - 842

[6] SORENSON HW, 1985, KALMAN FILTERING THE

[7] 1983, IEEE T AUTOMATIC CON, V28

[1] Gelb A, 1992, APPL OPTIMAL ESTIMAT

[2] Haykin S., 1986, ADAPTIVE FILTER THEO

[3] Kalman R.E., 1960, J BASIC ENG-T ASME, V82, P35, DOI [10.1115/1.3662552, DOI 10.1115/1.3662552]

[4] Kalman RE., 1961, T ASME D, V83, P95, DOI [DOI 10.1115/1.3658902, 10.1115/1.3658902]

[5] A DIRECT APPROACH TO IDENTIFY THE NOISE COVARIANCES OF KALMAN FILTERING [J]. IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 1980, 25 (04) : 841 - 842

[6] SORENSON HW, 1985, KALMAN FILTERING THE

[7] 1983, IEEE T AUTOMATIC CON, V28