Page 132 - Autonomous Mobile Robots
P. 132

Data Fusion via Kalman Filter                              115

                              Due to the differencing of measurements, this estimate is noisy; since I a changes
                              very slowly, it can be low-pass filtered to remove the noise. For measure-
                              ments from single frequency receivers, it is possible to compensate part of the
                              ionospheric delay errors by an ionospheric delay model [36]. Alternatively,
                              differential operation using at least two receivers can effectively remove all
                              common mode errors (i.e., c	t sv , I a , E cm ).
                                 The methods discussed in the subsequent sections can be used for the pseu-
                              dorange or integer-resolved carrier phase measurements. We will not discuss
                              Doppler measurements. To avoid redundant text for the code and integer-
                              resolved carrier measurements, we will adopt the following general model for
                              the range measurement to the ith satellite



                                                     2         2        2
                                         ˜ ρ i =  (X i − x) + (Y i − y) + (Z i − z) + b u + ε i  (3.44)
                                    ρ
                              where ˜ could represent the code pseudorange measurements or integer-
                              resolved carrier phase measurements. The variable b u represents the receiver
                              clock bias. The symbol ε represents the error terms appropriate for the different
                              measurements. When a GPS receiver has collected range measurements from
                              four or more satellites, it can calculate a navigation solution.


                              3.3.2 Single-Point GPS Navigation Solution

                              Thissection presentsthestandard GPS position solution method using nonlinear
                              least squares. In the process, we will introduce notation needed for the sub-
                                                                                           T
                              sequent sections. In this section, the state vector is defined as x =[x, y, z, b u ]
                              where (x, y, z) is the receiver antenna position in earth centered earth fixed
                              (ECEF) coordinates and b u is the receiver clock bias.
                                 Taylor series expansion of Equation (3.44) about the current state estimate
                                       ˆ
                              ˆ x =[ˆx, ˆy, ˆz, b u ] yields

                                              ˜ ρ i (x) =ˆρ i (ˆ x) +[h i ,1]δx + h.o.t.s + ε i

                              where

                                                                             ˆ
                                           δx = x − ˆ x =[x −ˆx, y −ˆy, z −ˆz, b u − b u ] T

                                                        2         2         2  ˆ
                                         ˜ ρ i (ˆ x) =  (X i −ˆx) + (Y i −ˆy) + (Z i −ˆz) + b u  (3.45)

                                                 ∂ρ i ∂ρ i ∂ρ i
                                           h i =    ,   ,
                                                  ∂x  ∂y ∂z
                                                              (ˆx,ˆy,ˆz)


                              © 2006 by Taylor & Francis Group, LLC



                                FRANKL: “dk6033_c003” — 2006/3/31 — 16:42 — page 115 — #17
   127   128   129   130   131   132   133   134   135   136   137