Patent Document ID: 8471764
Application ID: 12383507
Patent Flag: 1

Claim One:
1. A method for estimating hidden channel parameters, specifically delay, amplitude and phase, of a GNSS navigation signal received in a dynamic multipath environment, comprising: using a sequential estimation by means of a recursive Bayesian filtering which starts from a likelihood value of a measured channel output signal and updating said value using a state transition model, utilizing knowledge about statistic dependences of sets of time-varying channel parameters by introducing a movement model related to an actual channel environment, said movement model corresponding to a Markov process and forming a state transition model, utilizing knowledge that reflection signals typically have a life cycle starting from a first appearance and experiencing a change in delay, amplitude and phase over time until the reflection signals disappear, to form a prediction, and, estimating with said movement model as a basis, channel parameters sequentially by means of a recursive Bayesian filter, a number of paths being implicitly included in said step of estimating, wherein a result of said step of estimating is not only a fixed estimated value, but probability density functions of the estimated channel parameters, and using the estimated channel parameters for signal processing of a received GNSS signal in the dynamic multipath environment; wherein said movement model takes binding of a delay of a direct signal path into account via position parameters and clock parameters determined on a receiver side, wherein dynamic behavior of the dynamic channel parameters is approximated by a stochastic movement model having the following design: for each signal received, a delay of a direct signal τ 1,j,k at a receiver is given by position parameters p k r,x , p k r,y , p k r,z and clock error τ k r , since c - 1 ⁢ ( p k r , x - p j , k t , x ) 2 + ( p k r , y - p j , k t , y ) 2 + ( p k r , z - p j , k t , z ) 2 + τ k r - ɛ j , k = τ 1 , j , k and both source positions and correction terms are known; wherein the position parameters follow the following stochastic process: 
 p k r,x =p k−1 r,x +{dot over (p)} k−1 r,x ·Δt+n x 
 p k r,y =p k−1 r,y +{dot over (p)} k−1 r,y ·Δt+n y 
 p k r,z =p k−1 r,z +{dot over (p)} k−1 r,z ·Δt+n z wherein parameters {dot over (p)} k r,x , {dot over (p)} k r,y , {dot over (p)} k r,z describe a speed of the position parameters and follow the following process: 
 {dot over (p)} k r,x ={dot over (p)} k−1 r,x +n {dot over (x)} 
 {dot over (p)} k r,y ={dot over (p)} k−1 r,y +n {dot over (y)} 
 {dot over (p)} k r,z ={dot over (p)} k−1 r,z +n ż wherein the clock error follows the following stochastic process: 
 τ k r =τ k−1 r +τ k r ·Δt+n τ,r wherein parameter {dot over (τ)} k r describes a drift of a receiver clock and follows the following process: 
 {dot over (τ)} k r ={dot over (τ)} k−1 r +n {dot over (τ)},r wherein a multipath channel is characterized by a direct path and up to N m −1 echo signals; wherein at a time k, each path described by index i has a complex amplitude a i,j,k and a relative delay Δτ i,j,k =τ i,k −τ i,j,k , where the relative delays of echo signals can only assume positive values; wherein various relative path delays follow the following stochastic process: 
 τ i,j,k =τ i,j,k−1 +{dot over (τ)} i,j,k−1 ·Δt+n τ ,i> 1 wherein parameters {dot over (τ)} i,k describe a speed of the path delays of multipaths and follow the following process: 
 {dot over (τ)} i,j,k ={dot over (τ)} i,j,k−1 +n {dot over (τ)} ,i> 1 wherein a value and phase of individual paths, described by complex amplitudes α i,j,k , are eliminated by maximizing a likelihood function for given values τ i,j,k with respect to α i,j,k , which serves to reduce parameter space, aiming at a reduction of complexity; wherein every path may be specified by the parameter 
 e i,j,k ε{0≡“off”,1≡“on”} wherein values e i,j,k follow a simple Markov process with two states and asymmetric transition probabilities; and wherein the stochastic movement model includes two Gaussian noise sources n x , n y , n z , n {dot over (x)} , n {dot over (y)} , n ż , n τ,r , n {dot over (τ)},r , n τ , n {dot over (τ)} as well as a noise process for controlling state transitions for the values e i,j,k and wherein parameter Δτ refers to a time span between times k−1 and k.