Abstract: A method and corresponding devices for processing and transmitting information are described. A sequence of binary signals is mapped to symbols that forms a two-dimensional matrix of symbols in one of the frequency-time or time-time or time-frequency or frequency-frequency domain and which may be filtered in that domain. Selecting the diagonal elements of said matrix forms a transmit vector.

Abstract: A method for estimating hidden channel parameters of a GNSS navigation signal received in a multipath environment includes a sequential Bayesian estimation. A movement model forms the basis of the estimation and is designed especially for dynamic channel scenarios and takes into account the speeds of change and the variable life cycles of the path. The estimator is implemented as a recursive Bayesian filter for a combined determination of positions and suppression of multipaths. The binding of the delay of the direct path is taken into consideration via position and clock parameters. The method is carried out with GNSS satellite navigation receivers, e.g. GPS and Galileo. With the method, multipath error of received GNSS navigation signals is reduced. The multipath channel includes a direct path and Nm-I echo signals and each of these paths may be considered on or off for the estimation.

Abstract: For the reduction of the multipath error of received GNSS navigation signals, a sequential Bayesian estimation is used, with a movement model underlying this estimation, which model is particularly designed for dynamic channel situations. Sequential Monte Carlo methods are used to calculate the posterior probability density functions of the signal parameters. To facilitate an efficient integration in received signal tracking loops, the invention builds on complexity reduction concepts that have previously been used in maximum likelihood (ML) estimators. Applicable with GNSS satellite navigation receivers, e.g. GPS and Galileo.

Abstract: The method for estimating parameters of a navigation signal received by a receiver which receives navigation signals through a plurality of paths wherein the parameters include data modulated on the navigation signal and complex amplitudes i.e. amplitude and phase shift, and time delays of the individual paths, comprises receiving a navigation signal and sampling the received navigation signal. Moreover, the parameters are sequentially estimated in terms of a posterior probability density function. For facilitating the sequential estimation, the received vector is transformed into a compressed vector without loss of information by using a correlator bank having a plurality of correlator reference signals.

Abstract: For the reduction of the multipath error of received GNSS navigation signals, a sequential Bayesian estimation is used, with a movement model forming the basis of the estimation, which model is designed especially for dynamic channel scenarios and takes into account the speeds of change and the variable life cycles of the path. The estimator is implemented as a recursive Bayesian filter for a combined determination of positions and suppression of multipaths. The binding of the delay of the direct path is taken into consideration via position and clock parameters. Application with GNSS satellite navigation receivers, e.g. GPS and Galileo.

Abstract: For the reduction of the multipath error of received GNSS navigation signals, a sequential Bayesian estimation is used, with a movement model underlying this estimation, which model is particularly designed for dynamic channel situations. Sequential Monte Carlo methods are used to calculate the posterior probability density functions of the signal parameters. To facilitate an efficient integration in received signal tracking loops, the invention builds on complexity reduction concepts that have previously been used in maximum likelihood (ML) estimators. Applicable with GNSS satellite navigation receivers, e.g. GPS and Galileo.

Abstract: The method for estimating parameters of a navigation signal received by a receiver which receives navigation signals through a plurality of paths wherein the parameters include data modulated on the navigation signal and complex amplitudes i.e. amplitude and phase shift, and time delays of the individual paths, comprises receiving a navigation signal and sampling the received navigation signal. Moreover, the parameters are sequentially estimated in terms of a posterior probability density function. For facilitating the sequential estimation, the received vector is transformed into a compressed vector without loss of information by using a correlator bank having a plurality of correlator reference signals.