The efficiency of using a linearized, an iterated and an optimal linear algorithms for the solution of nonlinear navigation problems is analyzed. The emphasis is on the problem of deriving an adequate accuracy charact...
详细信息
The efficiency of using a linearized, an iterated and an optimal linear algorithms for the solution of nonlinear navigation problems is analyzed. The emphasis is on the problem of deriving an adequate accuracy characteristic. The comparison of is carried out by the example of solving problems of navigation by beacons and terrain-aided navigation with the use of a map. The results are given, illustrating the advantages of the linear optimal algorithm both from the accuracy standpoint and the standpoint of adequacy of the covariance matrix being generated.
This correspondence presents a new recursive least squares (RLS) adaptive algorithm. The proposed computational scheme uses a finite window by means of a lemma for the system matrix inversion that is, for the first ti...
详细信息
This correspondence presents a new recursive least squares (RLS) adaptive algorithm. The proposed computational scheme uses a finite window by means of a lemma for the system matrix inversion that is, for the first time, stated and proven here. The new algorithm has excellent tracking capabilities. Moreover, its particular structure allows for stabilization by means of a quite simple method. Its stabilized version performs very well not only for a white noise input but also for nonstationary inputs as well. It is shown to follow music, speech, environmental noise, etc, with particularly good tracking properties. The new algorithm can be parallelized via a simple technique. Its parallel form is very fast when implemented with four processors.
暂无评论