Troubleshooting Kalman Filtering for INS/GPS Integration

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SUMMARY

The discussion focuses on troubleshooting the implementation of Kalman filtering in an Inertial Navigation System (INS) integrated with GPS. The user references the equations from "Strapdown Inertial Navigation," specifically the discrete Kalman filter equations, and expresses confusion regarding the calculation of the system transition matrix (FF). The user seeks clarification on how to programmatically realize FF = exp[F(t(k+1) - tk)], which is essential for constructing a discrete Kalman filter.

PREREQUISITES
  • Understanding of Kalman filtering principles and equations
  • Familiarity with INS and GPS integration techniques
  • Knowledge of matrix operations and exponential functions in programming
  • Experience with programming languages suitable for numerical computations (e.g., Python, MATLAB)
NEXT STEPS
  • Research the implementation of matrix exponentiation in programming languages like Python using libraries such as NumPy
  • Study the derivation and application of the system transition matrix (FF) in discrete Kalman filters
  • Explore advanced Kalman filter techniques, including Extended Kalman Filters (EKF) for non-linear systems
  • Review case studies or examples of INS/GPS integration using Kalman filtering to understand practical applications
USEFUL FOR

This discussion is beneficial for engineers and developers working on navigation systems, particularly those involved in the integration of inertial sensors with GPS, as well as researchers focusing on Kalman filtering techniques.

shtuceron
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Hello all.

I have some problem with realisation Kalman filtering in INS/GPS integration system.

I use equation from "Strapdown Inertial Navigaation" chapter 12. and trying programming Kalman filtering (discret), but have some trouble, estimate error have very small value on graphic, but error graphic have best result, why is it?

for example:
2qsml91.png
(if i zoom it is really good)Kalman filtering algorithm:

S = F*P*transpose(F) + G*Q*transpose(G);

K = S*transpose(H)*(H*S*transpose(H) + R)^-1;

Pout = (eye(15,15) - K*H)*S;

EXout = F*EX + K*(Z - H*F*EX);
 
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It seems that I can find mistake, I use dynamic matrix from chapter 12, but on 404 page (chapter 13) wrote, that:"in Oder to allow a discrete Kalman filter to be constructed, it is necessary to express the system error equation (13.1) in discrete form. If ex represents the inertial navigation system error states at time tk and t(k+1) the error states at time t(k+1) we may write: dx =FF*dx + wk, where FF is the system transition matrix at time tk, which may be expressed in terms of the system matrix F as follows: FF = exp[F(t(k+1) - tk)]"
my question : how can I realize FF = exp[F(t(k+1) - tk)] in programming?
 
Thanks, i'am solve my problems.
 

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