Michael Stevens

nalgebra 0.34

nalgebra 0.34

Document new_weights

Hello Adrain, I seen this too. The are lots of ways the sigma transformation can be parametrised. In my UKF implementation I try follow the numerics in various publications and implementations with alpha controlling the spread. The numerics don't seem to be great and I don't see a solution at the moment. If you can build Jacobians out of your hopefully not too non-linear model the the UD filter should be numerically stable. Nalgebra 0.34 is based on Rust edition 2024 which fit nicely with my recent...

Test unscented with alpha = 1e-3

Slightly improve new_weight to avoid a division

Interestingly the earlier Wan & Merwe paper 'The Unscented KalmanFilter for Nonlinear Estimation' has a 'kappa' in the formulation of weights. It has a completely different definition to that in the original Julier & Uhlman paper. They simply state 'kappa is a secondary scaling parameter which is usually set to 0'!

I've retested. 'simple_unscented' with alpha 1e-3 give identical results as alpha 1, which is to be expected as the 'simple' test is linear. 'rtheta_unscented' with alpha 1e-3 changes a little but looks reasonable. Since you are only having a problem in observe I wonder if the problem is related to the size of the observation vector. The test I have it only a two dimensional observation. What are the dimensions of your models. Is the observation function discontinues?