منابع مشابه
Continuous Time Particle Filtering
We present the continuous-time particle filter (CTPF) – an extension of the discrete-time particle filter for monitoring continuous-time dynamic systems. Our methods apply to hybrid systems containing both discrete and continuous variables. The dynamics of the discrete state system are governed by a Markov jump process. Observations of the discrete process are intermittent and irregular. Whenev...
متن کاملAdaptive Filtering of Continuous GPS Results
The dramatic decrease in the cost of Global Positioning System (GPS) receivers has made feasible the establishment of extensive Continuous GPS receiver arrays (CGPS), for the study of crustal deformation (and to support differential GPS applications). The GPS Earth Observation NETwork (GEONET) of the Geographical Survey Institute in Japan and the Southern California Integrated GPS Network (SCIG...
متن کاملDelay Spoofing Reduction in GPS Navigation System based on Time and Transform Domain Adaptive Filtering
Due to widespread use of Global Positioning System (GPS) in different applications, the issue of GPS signal interference cancelation is becoming an increasing concern. One of the most important intentional interferences is spoofing signals. An effective interference (delay spoof) reduction method based on adaptive filtering is developed in this paper. The principle of method is using adaptive f...
متن کاملFiltering in continuous time by least action
0. The reason I volunteered for the working group on continuous-time filtering problems was because it seemed to me that in the other areas probably the best you could hope to achieve was some improvement of existing ‘bread-and-butter’ SMC methods, whereas in continuous time there was much more scope for novelty. In particular, in continuous time you have all the tools of stochastic calculus, s...
متن کاملContinuous-time Errors-in-variables Filtering
We consider estimation problems for a continuous-time linear system with a state disturbance and additive errors on the input and the output. The problem formulation and the estimation principle are deterministic. The derived filter is identical to the stochastic Kalman filter. The problem formulation with additive error on both the input and the output, however, is more symmetric then the clas...
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ژورنال
عنوان ژورنال: IEEE Transactions on Automatic Control
سال: 1986
ISSN: 0018-9286
DOI: 10.1109/tac.1986.1104380