A practical guide to building Kalman filters, showing how the filtering equations can be applied to real-life problems. Numerous examples are presented in detail, and computer code written in FORTRAN, MATLAB and True BASIC accompanies all the examples.MATLAB Ar can generate Gaussian-distributed random numbers with a single statement. Figure 1.7 displays the values of each of the 1000 Gaussian random numbers, generated via the program of Listing 1.8, in graphic form. If a Gaussian ... 4-i 2- -2- a#39;4-. Listing 1.9 Program used to generate probability density function C.
|Title||:||Fundamentals of Kalman Filtering|
|Author||:||Paul Zarchan, Howard Musoff|
|Publisher||:||Amer Inst of Aeronautics & - 2000|