Differences

This shows you the differences between two versions of the page.

--- radar:tws [2018/06/08 10:17] – george
+++ radar:tws [2026/04/28 18:24] (current) – mauro
@@ Line 1: / Line 1: @@
->TOC ok for now! Please use headers instead of bold!  --- //[[webmaster@localhost|DokuWiki Administrator]] 2018/04/24 16:18//
 ===== TWS =====
@@ Line 560: / Line 560: @@
 mean square error in the smoothed position and velocity.
-When the Kalman filter is modeled with the target trajectory as a straight line , and the measurement noise and the trajectory disturbance are modeled as white , guassian noise with zero mean , the kalamn filter equations reduce to the α - β tracker equations with  α and  β computed sequentially by the kalman filter procedure.Blackman states that " Experience with airborne radars has shown the versatility of kalman filter to be almost indespensable when dealing with problems presented by missing data and variable measurement noise statics" . The kalman filter has better performance than the  α - β tracker since it utilizes more information. The  α - β tracker, however might be considered when the target's maneuver statistics are not known or in a dense target environment where computational simplicity is important. The Kalman filterand the  α - β tracker also can be applied to control digitally the feedback loop in the single target tracker. The Kalman filter is essentially a set of mathematical equations that implement a
+When the Kalman filter is modeled with the target trajectory as a straight line , and the measurement noise and the trajectory disturbance are modeled as white , guassian noise with zero mean , the kalamn filter equations reduce to the α - β tracker equations with  α and  β computed sequentially by the kalman filter procedure.Blackman states that " Experience with airborne radars has shown the versatility of kalman filter to be almost indespensable when dealing with problems presented by missing data and variable measurement noise statics" . The kalman filter has better performance than the  α - β tracker since it utilizes more information. The  α - β tracker, however might be considered when the target's maneuver statistics are not known or in a dense target environment where computational simplicity is important. The Kalman filter and the  α - β tracker also can be applied to control digitally the feedback loop in the single target tracker. The Kalman filter is essentially a set of mathematical equations that implement a
 predictor-corrector type estimator that is optimal in the sense that it minimizes the
 estimated error covariance—when some presumed conditions are met. Since the time of